Journal articles: 'Production scheduling Mathematics'

1

Budiyantoro and Y. Kerlooza. "Priority Strategy in Clothing Production Scheduling Using Mathematics Model." IOP Conference Series: Materials Science and Engineering 407 (September 26, 2018): 012142. http://dx.doi.org/10.1088/1757-899x/407/1/012142.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Huang, Min, Ruixian Huang, Bo Sun, and Linrong Li. "Research on the Production Scheduling Optimization for Virtual Enterprises." Mathematical Problems in Engineering 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/492158.

Full text

Abstract:

Production scheduling is a rather difficult problem in virtual enterprises (VE) for the tasks of production which would be executed by some distributed and independent members. Factors such as the timing constraints of task and ability restrictions of the members are considered comprehensibly to solve the global scheduling optimization problem. This paper establishes a partner selection model based on an improved ant colony algorithm at first, then presents a production scheduling framework with two layers as global scheduling and local scheduling for virtual enterprise, and gives a global scheduling mathematical model with the smallest total production time based on it. An improved genetic algorithm is proposed in the model to solve the time complexity of virtual enterprise production scheduling. The presented experimental results validate the optimization of the model and the efficiency of the algorithm.

APA, Harvard, Vancouver, ISO, and other styles

3

Bierwirth, Christian, and Dirk C. Mattfeld. "Production Scheduling and Rescheduling with Genetic Algorithms." Evolutionary Computation 7, no. 1 (March 1999): 1–17. http://dx.doi.org/10.1162/evco.1999.7.1.1.

Full text

Abstract:

A general model for job shop scheduling is described which applies to static, dynamic and non-deterministic production environments. Next, a Genetic Algorithm is presented which solves the job shop scheduling problem. This algorithm is tested in a dynamic environment under different workload situations. Thereby, a highly efficient decoding procedure is proposed which strongly improves the quality of schedules. Finally, this technique is tested for scheduling and rescheduling in a non-deterministic environment. It is shown by experiment that conventional methods of production control are clearly outperformed atreasonable runtime costs.

APA, Harvard, Vancouver, ISO, and other styles

4

Gao, Yan, Xin Zhang, and Jian Zhong Xu. "An Improved Production Scheduling Algorithm Based on Resource Constraints." Applied Mechanics and Materials 455 (November 2013): 619–24. http://dx.doi.org/10.4028/www.scientific.net/amm.455.619.

Full text

Abstract:

For resource-constrained project scheduling problems, with aircraft assembly as its background, we established its mathematics model as constraint satisfaction problem. An improved critical path scheduling algorithm is proposed, considering the constraints of precedence relations, resource constraints and space constraints, through the two stages of planning, reaching for aircraft assembly task scheduling optimization objectives. Through the given numerical example results show that, when the objective consists in minimizing the project duration, the algorithm has better performance.

APA, Harvard, Vancouver, ISO, and other styles

5

Zhu, Haihua, Yi Zhang, Changchun Liu, and Wei Shi. "An Adaptive Reinforcement Learning-Based Scheduling Approach with Combination Rules for Mixed-Line Job Shop Production." Mathematical Problems in Engineering 2022 (September 5, 2022): 1–14. http://dx.doi.org/10.1155/2022/1672166.

Full text

Abstract:

Affected by economic globalization and market diversification, more manufacturing enterprises realize that large-scale production cannot adapt to the current market environment. The new trend of multivariety customized mixed-line production brings a higher level of disturbances and uncertainties to production planning. Traditional methods cannot be directly applied to the classic flexible job shop scheduling problem (FJSP). Therefore, this paper presents an adaptive scheduling method for mixed-line job shop scheduling. First, the scheduling problem caused by combined processing constraints is studied and transformed by introducing the definition of virtual operation. According to the situation of the coexistence of trial-production and batch production, the disturbance processing mechanism is established. And a scheduling decision model is established based on contextual bands (CBs) in reinforcement learning to overcome the shortcoming of poor performance of traditional single dispatching rule strategy. Through continuous trial and error learning, each scheduler can select the most suitable scheduling rules according to the environment state. Finally, we benchmark the performance of the scheduling algorithm with scheduling methods based on a variety of single scheduling rules. The results show that the proposed algorithm not only improves the performance in the mixed production scheduling problem but also effectively copes with emergency trial-production orders.

APA, Harvard, Vancouver, ISO, and other styles

6

Zaremba, Marek B. "Scheduling of production processes." Control Engineering Practice 4, no. 1 (January 1996): 141–42. http://dx.doi.org/10.1016/s0967-0661(96)90035-0.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Aloise, Dario J., Daniel Aloise, Caroline T. M. Rocha, Celso C. Ribeiro, José C. Ribeiro Filho, and Luiz S. S. Moura. "Scheduling workover rigs for onshore oil production." Discrete Applied Mathematics 154, no. 5 (April 2006): 695–702. http://dx.doi.org/10.1016/j.dam.2004.09.021.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Chen, Xiaowu, Guozhang Jiang, Yongmao Xiao, Gongfa Li, and Feng Xiang. "A Hyper Heuristic Algorithm Based Genetic Programming for Steel Production Scheduling of Cyber-Physical System-ORIENTED." Mathematics 9, no. 18 (September 14, 2021): 2256. http://dx.doi.org/10.3390/math9182256.

Full text

Abstract:

Intelligent manufacturing is the trend of the steel industry. A cyber-physical system oriented steel production scheduling system framework is proposed. To make up for the difficulty of dynamic scheduling of steel production in a complex environment and provide an idea for developing steel production to intelligent manufacturing. The dynamic steel production scheduling model characteristics are studied, and an ontology-based steel cyber-physical system production scheduling knowledge model and its ontology attribute knowledge representation method are proposed. For the dynamic scheduling, the heuristic scheduling rules were established. With the method, a hyper-heuristic algorithm based on genetic programming is presented. The learning-based high-level selection strategy method was adopted to manage the low-level heuristic. An automatic scheduling rule generation framework based on genetic programming is designed to manage and generate excellent heuristic rules and solve scheduling problems based on different production disturbances. Finally, the performance of the algorithm is verified by a simulation case.

APA, Harvard, Vancouver, ISO, and other styles

9

Zandieh, M., and S. Molla-Alizadeh-Zavardehi. "Synchronizing production and air transportation scheduling using mathematical programming models." Journal of Computational and Applied Mathematics 230, no. 2 (August 2009): 546–58. http://dx.doi.org/10.1016/j.cam.2008.12.022.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Zhang, Tao, Yue Wang, Xin Jin, and Shan Lu. "Integration of Production Planning and Scheduling Based on RTN Representation under Uncertainties." Algorithms 12, no. 6 (June 10, 2019): 120. http://dx.doi.org/10.3390/a12060120.

Full text

Abstract:

Production planning and scheduling are important bases for production decisions. Concerning the traditional modeling of production planning and scheduling based on Resource-Task Network (RTN) representation, uncertain factors such as utilities are rarely considered as constraints. For the production planning and scheduling problem based on RTN representation in an uncertain environment, this paper formulates the multi-period bi-level integrated model of planning and scheduling, and introduces the uncertainties of demand and utility in planning and scheduling layers respectively. Rolling horizon optimization strategy is utilized to solve the bi-level integrated model iteratively. The simulation results show that the proposed model and algorithm are feasible and effective, can calculate the consumption of utility in every period, decrease the effects of uncertain factors on optimization results, more accurately describe the uncertain factors, and reflect the actual production process.

APA, Harvard, Vancouver, ISO, and other styles

11

Huo, Yumei, Joseph Y. T. Leung, and Xin Wang. "Integrated production and delivery scheduling with disjoint windows." Discrete Applied Mathematics 158, no. 8 (April 2010): 921–31. http://dx.doi.org/10.1016/j.dam.2009.12.010.

Full text

APA, Harvard, Vancouver, ISO, and other styles

12

Dunstall, Simon, and Graham Mills. "Robustness of cyclic schedules for the charging of batteries." ANZIAM Journal 48, no. 4 (April 2007): 475–92. http://dx.doi.org/10.1017/s1446181100003163.

Full text

Abstract:

AbstractIn 2002 the Mathematics in Industry Study Group (MISG) investigated the question of optimally scheduling cyclic production in a battery charging and finishing facility. The facility produces various types of battery and the scheduling objective is to maximize battery throughout subject to achieving a pre-specified product-mix. In this paper we investigate the robustness of such schedules using simulation experiments that span multiple production cycles. We simulate random variations (delays) in battery charging time and find that an optimal off-line schedule yields higher throughput in comparison to a common on-line dispatching rule. This result has been found to hold for a range of expected charging-time delays and has significant practical implications for scheduling battery charging and finishing facilities.

APA, Harvard, Vancouver, ISO, and other styles

13

Abedinnia, Hamid, Christoph H. Glock, and Michael D. Schneider. "Machine scheduling in production: A content analysis." Applied Mathematical Modelling 50 (October 2017): 279–99. http://dx.doi.org/10.1016/j.apm.2017.05.016.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Zhu, Kai. "A Joint Optimization Model of Production Scheduling and Maintenance Based on Data Driven for a Parallel-Series Production Line." Journal of Mathematics 2021 (September 27, 2021): 1–11. http://dx.doi.org/10.1155/2021/7588559.

Full text

Abstract:

The maintenance of a production line is becoming more important with the development of demanding higher operational efficiency and safety in industrial system. However, a production line often operates under dynamically operational and environmental conditions and the production scheduling is also a very important factor for the maintenance of a production line. First, this paper proposes an integrated data-driven model that coordinates maintenance planning decisions with production scheduling decisions to solve the problem of scheduling and maintenance planning for a parallel-series production line. The degradation information is considered, and the total cost is to be minimized in the proposed model. Also, the total cost is related with production process and maintenance considering reliability of equipment. Then, in order to better describe the relationship between production and maintenance, the accumulative processing time of equipment is used as the input of its failure function. Also, an ability factor is developed to control its reduced level by adopting preventive maintenance. Finally, a case study is used to demonstrate the implementation and potential applications of the proposed model. The long-term wear test experiments are conducted at a research laboratory facility of Shanghai Pangyuan Machinery Co., Ltd. The result proves that the proposed method is feasible and efficient to solve the joint decision-making problem for a parallel-series production line with multivariety and small batch production. The proposed model in this paper is suitable for semiconductor manufacturing.

APA, Harvard, Vancouver, ISO, and other styles

15

Kumral, Mustafa. "Robust stochastic mine production scheduling." Engineering Optimization 42, no. 6 (June 2010): 567–79. http://dx.doi.org/10.1080/03052150903353336.

Full text

APA, Harvard, Vancouver, ISO, and other styles

16

Carlier, Jacques, Aziz Moukrim, and Huang Xu. "The project scheduling problem with production and consumption of resources: A list-scheduling based algorithm." Discrete Applied Mathematics 157, no. 17 (October 2009): 3631–42. http://dx.doi.org/10.1016/j.dam.2009.02.012.

Full text

APA, Harvard, Vancouver, ISO, and other styles

17

Lowe, C., and J. D. Tedford. "Fuzzy Production Scheduling for JIT Manufacturing." Intelligent Automation & Soft Computing 3, no. 4 (January 1997): 319–29. http://dx.doi.org/10.1080/10798587.1997.10750711.

Full text

APA, Harvard, Vancouver, ISO, and other styles

18

da Silva, Felipe Augusto Moreira, Antonio Carlos Moretti, and Anibal Tavares de Azevedo. "A Scheduling Problem in the Baking Industry." Journal of Applied Mathematics 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/964120.

Full text

Abstract:

This paper addresses a scheduling problem in an actual industrial environment of a baking industry where production rates have been growing every year and the need for optimized planning becomes increasingly important in order to address all the features presented by the problem. This problem contains relevant aspects of production, such as parallel production, setup time, batch production, and delivery date. We will also consider several aspects pertaining to transportation, such as the transportation capacity with different vehicles and sales production with several customers. This approach studies an atypical problem compared to those that have already been studied in literature. In order to solve the problem, we suggest two approaches: using the greedy heuristic and the genetic algorithm, which will be compared to small problems with the optimal solution solved as an integer linear programming problem, and we will present results for a real example compared with its upper bounds. The work provides us with a new mathematical formulation of scheduling problem that is not based on traveling salesman problem. It considers delivery date and the profit maximization and not the makespan minimization. And it also provides an analysis of the algorithms runtime.

APA, Harvard, Vancouver, ISO, and other styles

19

Ma, Fei, Hong Gu, Wei Hua Xu, and Qin Qin Tao. "Application of Fuzzy Mathematics Model in Evaluating Order Priority." Applied Mechanics and Materials 742 (March 2015): 390–94. http://dx.doi.org/10.4028/www.scientific.net/amm.742.390.

Full text

Abstract:

The method of make-to-order has gradually become the primary mode of production. It is an extremely important ability for enterprises to make production scheduling and response to the changes of customer demand agiely. Therefore, this paper mainly deals with how to evaluating order priority in the mode of make-to-order. For this question, an evaluation index system and a model of fuzzy mathematic system evaluation are established. Through empirical analysis, the model and evaluation system are found feasible and valid.

APA, Harvard, Vancouver, ISO, and other styles

20

Zheng, Feifeng, Yinfeng Xu, and E. Zhang. "On-line production order scheduling with preemption penalties." Journal of Combinatorial Optimization 13, no. 2 (December 8, 2006): 189–204. http://dx.doi.org/10.1007/s10878-006-9027-3.

Full text

APA, Harvard, Vancouver, ISO, and other styles

21

Zhou, Yaqin, Junliang Wang, Peng Zhang, Pan Wang, Yingtao Lu, and Jie Zhang. "Research on dyeing workshop scheduling methods for knitted fabric production based on a multi-objective hybrid genetic algorithm." Measurement and Control 53, no. 7-8 (July 30, 2020): 1529–39. http://dx.doi.org/10.1177/0020294020944947.

Full text

Abstract:

As the most important core process in the dyeing and finishing workshop of knitting companies, the dyeing process has the characteristics of multi-variety, small-batch, parallel machine processing of multiple types, and high cost in equipment cleaning, which render the dyeing scheduling problem a bottleneck in the production management of a dyeing and finishing workshop. In this paper, the dyeing process scheduling problem in dyeing and finishing workshops is described and abstracted, and an optimized mathematical model of dyeing scheduling is constructed with the goal of minimizing the delay cost and switching cost. Constraints such as multiple types of equipment, equipment capacity, weights of orders and equipment cleaning time are considered. For the sub-problem of equipment scheduling in the dyeing scheduling problem, a heuristic rule that considers equipment utilization and order delay is proposed. For the sub-problem of order sorting of the equipment in the dyeing scheduling problem, a hybrid genetic algorithm with a variable neighbourhood search strategy has been designed to optimize sorting. The algorithm proposed in this paper has been demonstrated via case simulation to be effective in solving the scheduling problem in dyeing and finishing workshops.

APA, Harvard, Vancouver, ISO, and other styles

22

Chen, Yong, Feiyang Yu, Ziwen Cheng, Qiuxia Jin, Zhi Pei, and Wenchao Yi. "Academic Insights and Perspectives: Cellular Automata and Production Scheduling." Mathematical Problems in Engineering 2020 (August 6, 2020): 1–15. http://dx.doi.org/10.1155/2020/6327314.

Full text

Abstract:

The cellular automata algorithm is one of the most important developments recently and is becoming an area of great potential in scheduling problems. There has been an increase in the quality and quantity of publications related to this topic. To formally illustrate the research status of the cellular automata algorithm at the global level, bibliometric analysis was used based on the Web of Science and Scopus databases, and 3086 documents were retrieved from different countries and regions. Institutions, journals, authors, research areas, author keywords, and highly cited articles are discussed in detail. The results show that the USA and China are the dominant countries in this field. The USA is the most active country cooperating with other 47 countries or regions, especially with China. The Journal of Cellular Automata is the most productive journal in this field, and the Democritus University of Thrace is the most productive institution also with the highest h-index. “Computer Science” is the most investigated area, with 544 documents involved. In addition, the major topics focused by author keywords are “genetic algorithm,” “swarm intelligence,” and “evolutionary computation.” In addition, the cellular automata algorithm is viewed as a new and effective method to solve the scheduling problems in manufacturing system; meanwhile, historical developments of the application of cellular automata in scheduling are displayed and analyzed.

APA, Harvard, Vancouver, ISO, and other styles

23

Jiang, Yang, Qiulei Ding, Junhu Ruan, and Wenjuan Wang. "Combining prospect theory with fuzzy theory to handle disruption in production scheduling." Filomat 32, no. 5 (2018): 1649–56. http://dx.doi.org/10.2298/fil1805649j.

Full text

Abstract:

This paper focuses on revising a production scheduling that an unpredictable disruption happens after a subset of jobs has been processed. Under these circumstances, continuing with the original schedule will not be optimal. This paper combines prospect theory and fuzzy theory to present a recovery model to handle the disruption. The proposed model is different from most rescheduling approaches in that the difference between the original schedule and the recovery schedule is contained by taking human behavior into consideration. The computational result demonstrates that due to the tradeoff between all participators involved in production scheduling, our model is more effective than existing rescheduling approaches.

APA, Harvard, Vancouver, ISO, and other styles

24

Bortolossi, H. J., M. V. Pereira, and C. Tomei. "Optimal hydrothermal scheduling with variable production coefficient." Mathematical Methods of Operations Research (ZOR) 55, no. 1 (March 1, 2002): 11–36. http://dx.doi.org/10.1007/s001860200174.

Full text

APA, Harvard, Vancouver, ISO, and other styles

25

Alvarez, Esther. "Multi-plant production scheduling in SMEs." Robotics and Computer-Integrated Manufacturing 23, no. 6 (December 2007): 608–13. http://dx.doi.org/10.1016/j.rcim.2007.02.006.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Ferreira Bertulucci, Michael, Giovanna Abreu Alves, and Victor Claudio Bento de Camargo. "Mathematical modeling to optimize production planning and scheduling in a small foundry with multiple alternating furnaces." Revista Gestão da Produção Operações e Sistemas 16, no. 04 (December 13, 2021): 82–114. http://dx.doi.org/10.15675/gepros.v16i4.2818.

Full text

Abstract:

Purpose - This study presents an extension to a model in the literature for lot-sizing and scheduling in a small foundry with multiple alternate furnaces. The purpose of the model is to minimize delays and inventory costs. In addition, it determines the best use of the load capacity in the furnaces. Theoretical framework – Lot-sizing in foundries in the marketplace is a subject of academic interest due to its applicability and mathematical and computational complexity. Many papers address the production problem in foundries with a single furnace, however, few papers address the possibility of multiple furnaces. Design/methodology/approach - Mathematical modeling was used to represent the lot-sizing and scheduling problem in a small foundry. Data from the company's order books were collected and model validation questionnaires were applied. Findings - The extended model was able to generate good production plans at different planning horizons, with better performance than the current methods obtained by the company. Originality/value - the extension of the model contributes to the literature by addressing the existence of multiple non-simultaneous furnaces, a feature that has not been greatly explored. A comparison with other models is performed to indicate the most suitable model for actual application. Keywords: Alloys scheduling. Foundry. Lot size. Mixed integer programming.

APA, Harvard, Vancouver, ISO, and other styles

27

Akmal Khalid, Mohd Nor, and Umi Kalsom Yusof. "An Improved Immune Algorithms for Solving Flexible Manufacturing System Distributed Production Scheduling Problem Subjects to Machine Maintenance." International Journal of Mathematical Models and Methods in Applied Sciences 15 (March 26, 2021): 17–25. http://dx.doi.org/10.46300/9101.2021.15.4.

Full text

Abstract:

Competitiveness and rapid expansion of flexible manufacturing system (FMS) as one of the industrial alternatives has attracted many practitioners’ and academicians’ interest. Recent globalization events have further encouraged FMS development into distributed, self-reliant units of production center. The flexible manufacturing system in distributed system (FMSDS) considers multi-factory environments, where jobs are processed by a system of FMSs. FMSDS problems deal with the allocation of jobs to factories, independent assignment of job operation to the machines, and operations sequencing on the machine. Additionally, in many previous studies, impact of maintenance as one of the core parts of production scheduling has been neglected. This significantly affects the overall performance of the production scheduling. As such, maintenance has been considered in this paper as part of the production scheduling. The objective of this paper is to minimize the global makespan over all the factories. This paper proposes an Improved Immune Algorithm (IIA) to solve the FMSDS problem. Antibody encoding adoption explicitly represents the information of factory, job, and maintenance, whilst a greedy decoding procedure exploits flexibility and determines the job routing. Rather than s traditional mutation operator, an improvised mutation operator is used to improve the solutions by refining the most promising individuals of each generation. The proposed approach has been compared with other algorithms and obtained satisfactory results, where the algorithm performance has been tested with several parameter tunings.

APA, Harvard, Vancouver, ISO, and other styles

28

Che, Ada, and Chengbin Chu. "Optimal Scheduling of Material Handling Devices in a PCB Production Line: Problem Formulation and a Polynomial Algorithm." Mathematical Problems in Engineering 2008 (2008): 1–21. http://dx.doi.org/10.1155/2008/364279.

Full text

Abstract:

Modern automated production lines usually use one or multiple computer-controlled robots or hoists for material handling between workstations. A typical application of such lines is an automated electroplating line for processing printed circuit boards (PCBs). In these systems, cyclic production policy is widely used due to large lot size and simplicity of implementation. This paper addresses cyclic scheduling of a multihoist electroplating line with constant processing times. The objective is to minimize the cycle time, or equivalently to maximize the production throughput, for a given number of hoists. We propose a mathematical model and a polynomial algorithm for this scheduling problem. Computational results on randomly generated instances are reported.

APA, Harvard, Vancouver, ISO, and other styles

29

Hauptman, Boštjan, and Vladimir Jovan. "An approach to process production reactive scheduling." ISA Transactions 43, no. 2 (April 2004): 305–18. http://dx.doi.org/10.1016/s0019-0578(07)60039-1.

Full text

APA, Harvard, Vancouver, ISO, and other styles

30

Zhao, Ning. "SCHEDULING IN FLEXIBLE MANUFACTURING LINE ORIENTING MATCHING PRODUCTION." Chinese Journal of Mechanical Engineering 41, no. 07 (2005): 180. http://dx.doi.org/10.3901/jme.2005.07.180.

Full text

APA, Harvard, Vancouver, ISO, and other styles

31

Costantino, Francesco, Alberto Felice De Toni, Giulio Di Gravio, and Fabio Nonino. "Scheduling Mixed-Model Production on Multiple Assembly Lines with Shared Resources Using Genetic Algorithms: The Case Study of a Motorbike Company." Advances in Decision Sciences 2014 (October 2, 2014): 1–11. http://dx.doi.org/10.1155/2014/874031.

Full text

Abstract:

The authors deal with the topic of the final assembly scheduling realized by the use of genetic algorithms (GAs). The objective of the research was to study in depth the use of GA for scheduling mixed-model assembly lines and to propose a model able to produce feasible solutions also according to the particular requirements of an important Italian motorbike company, as well as to capture the results of this change in terms of better operational performances. The “chessboard shifting” of work teams among the mixed-model assembly lines of the selected company makes the scheduling problem more complex. Therefore, a complex model for scheduling is required. We propose an application of the GAs in order to test their effectiveness to real scheduling problems. The high quality of the final assembly plans with high adherence to the delivery date, obtained in a short elaboration time, confirms that the choice was right and suggests the use of GAs in other complex manufacturing systems.

APA, Harvard, Vancouver, ISO, and other styles

32

Voronova, Anna, Ol'ga Kunickaya, Daria Burmistrova, Tamara Storodubtseva, Svetlana Chzhan, Valentina Nikiforova, Viktoria Shvetsova, and Evgenii Kalita. "Mobile Chipper Scheduling in the Production of Fuel Chips." Mathematical Modelling of Engineering Problems 9, no. 2 (April 28, 2022): 425–30. http://dx.doi.org/10.18280/mmep.090217.

Full text

Abstract:

Due to economic and environmental factors, boiler houses are forced to switch to wood fuel, which is very popular in the modern world. The most practical way to supply them with wood fuel is to mobilize mobile chippers that can move between different boiler houses and save money on additional chipping equipment. This paper seeks to build a mathematical model to optimize the movement of a mobile chipper between multiple boiler houses and its operation during the heating season. The model was designed for long-term planning, and it relies on a simplex algorithm. It considers three crucial parameters: machine capacity, feedstock amount, and traveled distance, and is suitable for schedule modeling purposes in the presence of fewer than 12 nodes. The number of nodes can be higher after a heuristic rule is applied. The proposal can be help schedule the biomass feedstock development at the regional level and switch to the local types of fuel. In addition, it will reduce the cost of thermal energy and increase the volume of wood waste chipped.

APA, Harvard, Vancouver, ISO, and other styles

33

Pan, Fucheng, and Yongqing Jiang. "Improved heuristic algorithm for modern industrial production scheduling." International Journal of Modelling, Identification and Control 30, no. 4 (2018): 284. http://dx.doi.org/10.1504/ijmic.2018.10016897.

Full text

APA, Harvard, Vancouver, ISO, and other styles

34

Lei, Deming, and Jingcao Cai. "Multi-population meta-heuristics for production scheduling: A survey." Swarm and Evolutionary Computation 58 (November 2020): 100739. http://dx.doi.org/10.1016/j.swevo.2020.100739.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

Tang, Qi, and Yiran Wang. "A Model Predictive Control for Lot Sizing and Scheduling Optimization in the Process Industry under Bidirectional Uncertainty of Production Ability and Market Demand." Computational Intelligence and Neuroscience 2022 (September 30, 2022): 1–23. http://dx.doi.org/10.1155/2022/2676545.

Full text

Abstract:

In the face of bidirectional uncertainty of market demand and production ability, this paper establishes a multiobjective mathematical model for lot sizing and scheduling integrated optimization of the process industry considering both material network and production manufacturing and finds the optimal decision of the model through model predictive control to minimize total completion time and total production cost. While realizing the model predictive control proposed in this paper, the Elman neural network predicts the relevant parameters required by learning historical orders for the uncertain market demand and equipment production ability. Then, the calculation formulas of product supply and demand matching and equipment production ability are formed and introduced into the next stage of the model as a constraint condition. In addition to the above constraints for constructing lot sizing and scheduling integrated models in the process industry, this paper also considers both the material network and production manufacturing and uses the IMOPSO algorithm to solve the problem iteratively. So far, a complete model predictive control can be generated. Through the model predictive control, the production system can respond in advance, make appropriate changes to offset the foreseeable interference, and obtain the lot sizing and scheduling scheme considering bidirectional uncertainty, thereby improving the system’s overall robustness. Finally, this paper realizes the model's predictive control process through example simulation and analyzes the operation results combined with the scheduling Gantt chart to verify the applicability and effectiveness of the model.

APA, Harvard, Vancouver, ISO, and other styles

36

Kong, Tengqiao, Dong Ren Nhg, and Van Tinh Shi. "Method for Optimizing Energy Consumption in Machining Manufacturing Process." Mathematical Problems in Engineering 2022 (May 23, 2022): 1–8. http://dx.doi.org/10.1155/2022/8300666.

Full text

Abstract:

With the rapid development of the economy and the continuous maturity of various industries and departments, the total amount of energy required by enterprises in the process of production and operation is also increasing year by year. To achieve sustainable development, it is necessary to adjust the current production and operation mode, reasonably evaluate the current state of resources, use advanced technology to optimize each link of production, and regard low-energy consumption and low carbon as the key to production improvement. In this paper, the integrated realization method of process planning and production scheduling based on intelligent algorithm is adopted, and the integrated model is solved by using the chromosome hierarchical coding genetic algorithm. When the alternative process schemes generated for each part through nonlinear process planning are given, the integrated model can weigh the optimization objectives and decide the suitable process route, machine tool selection scheme, and corresponding production scheduling scheme for each part. In this paper, a case study on the energy-saving effect of energy consumption optimization methods in machining and manufacturing processes is carried out. Taking a manufacturing enterprise as the background, the effectiveness of the proposed energy-saving method is verified by comparing the energy consumption of a batch of mechanical product parts in the process planning and production scheduling integrated mode and the traditional serial working mode.

APA, Harvard, Vancouver, ISO, and other styles

37

Tsai, Horng-Ren, and Toly Chen. "A Fuzzy Nonlinear Programming Approach for Optimizing the Performance of a Four-Objective Fluctuation Smoothing Rule in a Wafer Fabrication Factory." Journal of Applied Mathematics 2013 (2013): 1–15. http://dx.doi.org/10.1155/2013/720607.

Full text

Abstract:

In theory, a scheduling problem can be formulated as a mathematical programming problem. In practice, dispatching rules are considered to be a more practical method of scheduling. However, the combination of mathematical programming and fuzzy dispatching rule has rarely been discussed in the literature. In this study, a fuzzy nonlinear programming (FNLP) approach is proposed for optimizing the scheduling performance of a four-factor fluctuation smoothing rule in a wafer fabrication factory. The proposed methodology considers the uncertainty in the remaining cycle time of a job and optimizes a fuzzy four-factor fluctuation-smoothing rule to sequence the jobs in front of each machine. The fuzzy four-factor fluctuation-smoothing rule has five adjustable parameters, the optimization of which results in an FNLP problem. The FNLP problem can be converted into an equivalent nonlinear programming (NLP) problem to be solved. The performance of the proposed methodology has been evaluated with a series of production simulation experiments; these experiments provide sufficient evidence to support the advantages of the proposed method over some existing scheduling methods.

APA, Harvard, Vancouver, ISO, and other styles

38

Wu, Kun-Shan. "An optimal production scheduling policy for deteriorating items with time-varying production and demand rate." Journal of Interdisciplinary Mathematics 3, no. 1 (February 2000): 93–107. http://dx.doi.org/10.1080/09720502.2000.10700274.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Xue, Hai, Xuerui Zhang, Yasuhiro Shimizu, and Shigeru Fujimura. "Conception of self-construction production scheduling system." Electronics and Communications in Japan 93, no. 1 (January 2010): 19–29. http://dx.doi.org/10.1002/ecj.10188.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

Burkarda, Rainer E., Mihály Hujterb, Bettina Klinz, Rüdiger Rudolf, and Marc Wennink. "A process scheduling problem arising from chemical production planning." Optimization Methods and Software 10, no. 2 (January 1998): 175–96. http://dx.doi.org/10.1080/10556789808805710.

Full text

APA, Harvard, Vancouver, ISO, and other styles

41

He, Jianjia, Jian Wu, Ye Zhang, Yaopeng Wang, and Hua He. "Large-Scale Customized Production Scheduling of Multiagent-Based Medical 3D Printing." Computational Intelligence and Neuroscience 2022 (July 18, 2022): 1–13. http://dx.doi.org/10.1155/2022/6557137.

Full text

Abstract:

Three-dimensional (3D) printing, also known as additive manufacturing, has unique advantages over traditional manufacturing technologies; thus, it has attracted widespread attention in the medical field. Especially in the context of the frequent occurrence of major public health events, where the medical industry’s demand for large-scale and customized production is increasing, traditional 3D printing production scheduling methods take a long time to handle large-scale customized medical 3D printing (M-3DP) production and have weak intelligent collaboration ability in the face of job-to-device matching under multimaterial printing. Given the problem caused by M-3DP large-scale customized production scheduling, an intelligent collaborative scheduling multiagent-based method is proposed in this study. First, a multiagent-based optimization model is established. On this basis, an improved genetic algorithm embedded with the product mix strategy and the intelligent matching mechanism is designed to optimize the completion time and load balance between devices. Finally, the effectiveness of the proposed method is evaluated using numerical simulation. The simulation results indicated that compared with the simple genetic algorithm, particle swarm optimization, and snake optimizer, the improved genetic algorithm could better reduce the M-3DP mass customization production scheduling time, optimize the load balance between devices, and promote the “intelligent manufacturing” process of M-3DP mass customization.

APA, Harvard, Vancouver, ISO, and other styles

42

Schumacher, Christin, and Peter Buchholz. "Scheduling Algorithms for a Hybrid Flow Shop under Uncertainty." Algorithms 13, no. 11 (October 31, 2020): 277. http://dx.doi.org/10.3390/a13110277.

Full text

Abstract:

In modern production systems, scheduling problems have to be solved in consideration of frequently changing demands and varying production parameters. This paper presents a approach combining forecasting and classification techniques to predict uncertainty from demands, and production data with heuristics, metaheuristics, and discrete event simulation for obtaining machine schedules. The problem is a hybrid flow shop with two stages, machine qualifications, skipping stages, and uncertainty in demands. The objective is to minimize the makespan. First, based on the available data of past orders, jobs that are prone to fluctuations just before or during the production phase are identified by clustering algorithms, and production volumes are adjusted accordingly. Furthermore, the distribution of scrap rates is estimated, and the quantiles of the resulting distribution are used to increase corresponding production volumes to prevent costly rescheduling resulting from unfulfilled demands. Second, Shortest Processing Time (SPT), tabu search, and local search algorithms are developed and applied. Third, the best performing schedules are evaluated and selected using a detailed simulation model. The proposed approach is validated on a real-world production case. The results show that the price for a very robust schedule that avoids underproduction with a high probability can significantly increase the makespan.

APA, Harvard, Vancouver, ISO, and other styles

43

Kang, Lu, Ding Liu, Yali Wu, and Guozheng Ping. "Two-Stage Hybrid Optimization Algorithm for Silicon Single Crystal Batch Scheduling Problem under Fuzzy Processing Time." Mathematical Problems in Engineering 2023 (January 17, 2023): 1–14. http://dx.doi.org/10.1155/2023/3816574.

Full text

Abstract:

Considering the widely existing processing time uncertainty in the real-world production process, this paper constructs a fuzzy mathematical model for the silicon single crystal production batch scheduling problem to minimize the maximum completion time. In this paper, a two-stage hybrid optimization algorithm (TSHOA) is proposed for solving the scheduling model. Firstly, the improved differential evolution algorithm (IDE) is used to solve the order quantity allocation problem of silicon single crystal with different sizes to obtain the quantity of silicon single crystal rods with different sizes produced by different types of single crystal furnaces. Secondly, the variable neighborhood search (VNS) algorithm is adopted to optimize the order quantity sequencingof batch production processes. Finally, simulations and comparisons demonstrate the feasibility of the model and the effectiveness of TSHOA.

APA, Harvard, Vancouver, ISO, and other styles

44

Huang, Rong-Hwa, Tung-Han Yu, and Chen-Yun Lee. "Rolling Supply Chain Scheduling considering Suppliers, Production, and Delivery Lot-Size." Mathematical Problems in Engineering 2018 (September 30, 2018): 1–14. http://dx.doi.org/10.1155/2018/8601209.

Full text

Abstract:

Supply chain management and integration play a key factor in contemporary manufacturing concept. Companies seek to integrate itself within a cooperative and mutual benefiting supply chain. Supply chain scheduling, as an important aspect of supply chain management, highly emphasizes on minimizing stock costs and delivery costs. Most previous researches on supply chain scheduling problems assume make-to-order production, which includes delivery cost in lot-size. This practice simplifies the complexity of the problem. Instead, this research discusses make-to-contract production, where the supply chain has a rolling planning horizon that changes according to contracts. Within a planning horizon, two types of interval are defined. The first is frozen interval, in which the manufacturing decision cannot be changed. The second is free interval, where schedules can be adjusted depending on new contracts. This research aims to build a robust rolling supply management schedule to satisfy customers’ needs, by considering supplier, production, and delivery lot-size simultaneously. The objective is to effectively decide a combination of supplier, production, and delivery lot-size that minimizes total cost consisting of supplier cost, finish good stock cost, and delivery cost. Based on the concept, this study designs a problem-solving process that combines the methods of rolling planning horizon and genetic algorithm. Delivery size (DS), finish good stock (FS), and early delivery cost (ED) are the three methods applied; each will provide a guideline to produce a feasible solution. By further considering the fluctuations in practical needs and performing an overall evaluation, a robust and optimal supply chain scheduling plan can be decided, including the optimal lot-sizes of supplier, production, and delivery. In the effectiveness test which considers 3 types of customer demands and 11 types of company cost structures, the simulated data test results suggest that the proposed methods in this study have excellent performance.

APA, Harvard, Vancouver, ISO, and other styles

45

Tu, Ying-Mei. "Short-Term Scheduling Model of Cluster Tool in Wafer Fabrication." Mathematics 9, no. 9 (May 1, 2021): 1029. http://dx.doi.org/10.3390/math9091029.

Full text

Abstract:

Since last decade, the cluster tool has been mainstream in modern semiconductor manufacturing factories. In general, the cluster tool occupies 60% to 70% of production machines for advanced technology factories. The most characteristic feature of this kind of equipment is to integrate the relevant processes into one single machine to reduce wafer transportation time and prevent wafer contaminations as well. Nevertheless, cluster tools also increase the difficulty of production planning significantly, particularly for shop floor control due to complicated machine configurations. The main objective of this study is to propose a short-term scheduling model. The noteworthy goal of scheduling is to maximize the throughput within time constraints. There are two modules included in this scheduling model—arrival time estimation and short-term scheduling. The concept of the dynamic cycle time of the product’s step is applied to estimate the arrival time of the work in process (WIP) in front of machine. Furthermore, in order to avoid violating the time constraint of the WIP, an algorithm to calculate the latest time of the WIP to process on the machine is developed. Based on the latest process time of the WIP and the combination efficiency table, the production schedule of the cluster tools can be re-arranged to fulfill the production goal. The scheduling process will be renewed every three hours to make sure of the effectiveness and good performance of the schedule.

APA, Harvard, Vancouver, ISO, and other styles

46

Alhamad, Khaled, Rym M’Hallah, and Cormac Lucas. "A Mathematical Program for Scheduling Preventive Maintenance of Cogeneration Plants with Production." Mathematics 9, no. 14 (July 20, 2021): 1705. http://dx.doi.org/10.3390/math9141705.

Full text

Abstract:

This paper considers the scheduling of preventive maintenance for the boilers, turbines, and distillers of power plants that produce electricity and desalinated water. It models the problem as a mathematical program (MP) that maximizes the sum of the minimal ratios of production to the demand of electricity and water during a planning time horizon. This objective encourages the plants’ production and enhances the chances of meeting consumers’ needs. It reduces the chance of power cuts and water shortages that may be caused by emergency disruptions of equipment on the network. To assess its performance and effectiveness, we test the MP on a real system consisting of 32 units and generate a preventive maintenance schedule for a time horizon of 52 weeks (one year). The generated schedule outperforms the schedule established by experts of the water plant; it induces, respectively, 16% and 12% increases in the surpluses while either matching or surpassing the total production. The sensitivity analysis further indicates that the generated schedule can handle unforeseen longer maintenance periods as well as a 120% increase in demand—a sizable realization in a country that heavily relies on electricity to acclimate to the harsh weather conditions. In addition, it suggests the robustness of the schedules with respect to increased demand. In summary, the MP model yields optimal systematic sustainable schedules.

APA, Harvard, Vancouver, ISO, and other styles

47

Li, Haolin. "ALGORITHM OF FMS PRODUCTION SCHEDULING BASED ON GENETIC ALGORITHM." Chinese Journal of Mechanical Engineering 36, no. 09 (2000): 91. http://dx.doi.org/10.3901/jme.2000.09.091.

Full text

APA, Harvard, Vancouver, ISO, and other styles

48

ZHANG, Jie. "DOUBLE-FEEDBACK AND PHASES BASED SCHEDULING FOR FIRER PRODUCTION." Chinese Journal of Mechanical Engineering 42, no. 11 (2006): 125. http://dx.doi.org/10.3901/jme.2006.11.125.

Full text

APA, Harvard, Vancouver, ISO, and other styles

49

Zhao, Anran, Peng Liu, Xiyu Gao, Guotai Huang, Xiuguang Yang, Yuan Ma, Zheyu Xie, and Yunfeng Li. "Data-Mining-Based Real-Time Optimization of the Job Shop Scheduling Problem." Mathematics 10, no. 23 (December 5, 2022): 4608. http://dx.doi.org/10.3390/math10234608.

Full text

Abstract:

In the job-shop scheduling field, timely and proper updating of the original scheduling strategy is an effective way to avoid the negative impact of disturbances on manufacturing. In this paper, a pure reactive scheduling method for updating the scheduling strategy is proposed to deal with the disturbance of the uncertainty of the arrival of new jobs in the job shop. The implementation process is as follows: combine data mining, discrete event simulation, and dispatching rules (DRs), take makespan and machine utilization as scheduling criteria, divide the manufacturing system production period into multiple scheduling subperiods, and build a dynamic scheduling model that assigns DRs to subscheduling periods in real-time; the scheduling strategies are generated at the beginning of each scheduling subperiod. The experiments showed that the method proposed enables a reduction in the makespan of 2–17% and an improvement in the machine utilization of 2–21%. The constructed scheduling model can assign the optimal DR to each scheduling subperiod in real-time, which realizes the purpose of locally updating the scheduling strategy and enhancing the overall scheduling effect of the manufacturing system.

APA, Harvard, Vancouver, ISO, and other styles

50

Ma, Li, Minghan Xin, Yi-Jia Wang, and Yanjiao Zhang. "Dynamic Scheduling Strategy for Shared Agricultural Machinery for On-Demand Farming Services." Mathematics 10, no. 21 (October 23, 2022): 3933. http://dx.doi.org/10.3390/math10213933.

Full text

Abstract:

With the development of the “Internet +” model and the sharing economy model, the “online car-hailing” operation model has promoted the emergence of “online-hailing agricultural machinery”. This new supply and demand model of agricultural machinery has brought greater convenience to the marketization of agricultural machinery services. However, although this approach has solved the use of some agricultural machinery resources, it has not yet formed a scientific and systematic scheduling model. Referring to the existing agricultural machinery scheduling modes and the actual demand of agricultural production, based on the idea of resource sharing, in this research, the soft and hard time windows were combined to carry out the research on the dynamic demand scheduling strategy of agricultural machinery. The main conclusions obtained include: (1) Based on the ideas of order resource sharing and agricultural machinery resource sharing, a general model of agricultural machinery scheduling that meet the dynamic needs was established, and a more scientific scheduling plan was proposed; (2) Based on the multi-population coevolutionary genetic algorithm, the dynamic scheduling scheme for shared agricultural machinery for on-demand farming services was obtained, which can reasonably insert the dynamic orders on the basis of the initial scheduling scheme, and realize the timely response to farmers’ operation demands; (3) By comparing with the actual production situation, the path cost and total operating cost were saved, thus the feasibility and effectiveness of the scheduling model were clarified.

APA, Harvard, Vancouver, ISO, and other styles

Journal articles on the topic 'Production scheduling Mathematics'

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles