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Dissertations / Theses on the topic 'Production scheduling Mathematics'

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Author: Grafiati

Published: 10 December 2022

Last updated: 29 January 2023

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1

Srinivasan, Sudharshana. "Spatial Scheduling Algorithms for Production Planning Problems." VCU Scholars Compass, 2014. http://scholarscompass.vcu.edu/etd/3406.

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Spatial resource allocation is an important consideration in shipbuilding and large-scale manufacturing industries. Spatial scheduling problems (SSP) involve the non-overlapping arrangement of jobs within a limited physical workspace such that some scheduling objective is optimized. Since jobs are heavy and occupy large areas, they cannot be moved once set up, requiring that the same contiguous units of space be assigned throughout the duration of their processing time. This adds an additional level of complexity to the general scheduling problem, due to which solving large instances of the problem becomes computationally intractable. The aim of this study is to gain a deeper understanding of the relationship between the spatial and temporal components of the problem. We exploit these acquired insights on problem characteristics to aid in devising solution procedures that perform well in practice. Much of the literature on SSP focuses on the objective of minimizing the makespan of the schedule. We concentrate our efforts towards the minimum sum of completion times objective and state several interesting results encountered in the pursuit of developing fast and reliable solution methods for this problem. Specifically, we develop mixed-integer programming models that identify groups of jobs (batches) that can be scheduled simultaneously. We identify scenarios where batching is useful and ones where batching jobs provides a solution with a worse objective function value. We present computational analysis on large instances and prove an approximation factor on the performance of this method, under certain conditions. We also provide greedy and list-scheduling heuristics for the problem and compare their objectives with the optimal solution. Based on the instances we tested for both batching and list-scheduling approaches, our assessment is that scheduling jobs similar in processing times within the same space yields good solutions. If processing times are sufficiently different, then grouping jobs together, although seemingly makes a more effective use of the space, does not necessarily result in a lower sum of completion times.

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2

Park, Malcolm McKenzie. "Flowshop sequencing : a graphical approach /." Connect to thesis, 1990. http://eprints.unimelb.edu.au/archive/00001755.

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3

Hardin, Jill Renea. "Resource-constrained scheduling and production planning : linear programming-based studies." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/24857.

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4

Shieh, Alireza. "A simulated annealing approach for flexible flowshop scheduling to maximize flexibility." Morgantown, W. Va. : [West Virginia University Libraries], 2004. https://etd.wvu.edu/etd/controller.jsp?moduleName=documentdata&jsp%5FetdId=18.

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Thesis (M.S.)--West Virginia University, 2004.
Title from document title page. Document formatted into pages; contains xii, 112 p. : ill. Includes abstract. Includes bibliographical references (p. 95-99).

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5

Crowder, Bret. "Minimizing the makespan in a flexible flowshop with sequence dependent setup times, uniform machines, and limited buffers." Morgantown, W. Va. : [West Virginia University Libraries], 2006. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=4521.

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Thesis (M.S.)--West Virginia University, 2006.
Title from document title page. Document formatted into pages; contains viii, 136 p. : ill. Includes abstract. Includes bibliographical references (p. 96-106).

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6

Possani, Edgar. "Lot streaming and batch scheduling : splitting and grouping jobs to improve production efficiency." Thesis, University of Southampton, 2001. https://eprints.soton.ac.uk/50621/.

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This thesis deals with issues arising in manufacturing, in particular related to production efficiency. Lot streaming refers to the process of splitting jobs to move production through several stages as quickly as possible, whereas batch scheduling refers to the process of grouping jobs to improve the use of resources and customer satisfaction. We use a network representation and critical path approach to analyse the lot streaming problem of finding optimal sublot sizes and a job sequence in a two-machine flow shop with transportation and setup times. We introduce a model where the number of sublots for each job is not predetermined, presenting an algorithm to assign a new sublot efficiently, and discuss a heuristic to assign a fixed number of sublots between jobs. A model with several identical jobs in an multiple machine flow shop is analysed through a dominant machine approach to find optimal sublot sizes for jobs. For batch scheduling, we tackle the NP-hard problem of scheduling jobs on a batching machine with restricted batch size to minimise the maximum lateness. We design a branch and bound algorithm, and develop local search heuristics for the problem. Different neighbourhoods are compared, one of which is an exponential sized neighbourhood that can be searched in polynomial time. We develop dynamic programming algorithms to obtain lower bounds and explore neighbourhoods efficiently. The performance of the branch and bound algorithm and the local search heuristics is assessed and supported by extensive computational tests.

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7

Bester, Margarete Joan. "Design of an automated decision support system for scheduling tasks in a generalized job-shop." Thesis, Stellenbosch : Stellenbosch University, 2006. http://hdl.handle.net/10019.1/21734.

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8

Burdett, Robert. "Sequencing and scheduling theory for mixed-model multi-stage assembly environment." Thesis, Queensland University of Technology, 2001.

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9

Britton, Matthew Scott. "Stochastic task scheduling in time-critical information delivery systems." Title page, contents and abstract only, 2003. http://web4.library.adelaide.edu.au/theses/09PH/09phb8629.pdf.

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"January 2003" Includes bibliographical references (leaves 120-129) Presents performance analyses of dynamic, stochastic task scheduling policies for a real- time-communications system where tasks lose value as they are delayed in the system.

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10

Na, Byungsoo. "Optimization of automated float glass lines." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/39637.

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Motivated by operational issues in real-world glass manufacturing, this thesis addresses a problem of laying out and sequencing the orders so as to minimize wasted glass, called scrap. This optimization problem combines aspects of traditional cutting problems and traditional scheduling and sequencing problems. In so far as we know, the combination of cutting and scheduling has not been modeled, or solved. We propose a two-phase approach: snap construction and constructing cutting and offload schedules. Regarding the second phase problem, we introduce FGSP (float glass scheduling problem), and provide its solution structure, called coveys. We analyze simple sub-models of FGSP considering the main elements: time, unit, and width. For each model, we provide either a polynomial time algorithm or a proof of NP-completeness. Since FGSP is NP-complete, we propose a heuristic algorithm, Longest Unit First (LUF), and analyze the worst case performance of the algorithm in terms of the quality of solutions; the worst case performance bound is {1+(m-1)/m}+{1/3-1/(3m)} where m is the number of machines. It is 5/3 when m=2. For the real-world problem, we propose two different methods for snap construction, and we apply two main approaches to solve cutting and offloading schedules: an MIP approach and a heuristic approach. Our solution approach produces manufacturing yields greater than 99%; current practice is about 95%. This is a significant improvement and these high-yield solutions can save millions of dollars.

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11

Cross, Fionnuala Mary. "A model for loading and sequencing a flexible manufacturing cell." Thesis, Georgia Institute of Technology, 1986. http://hdl.handle.net/1853/25656.

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12

Li, Caiwei. "Dynamic scheduling of multiclass queueing networks." Diss., Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/24339.

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13

Summers, Deborah A. "Use of optimization models to solve labor planning and scheduling problems for the service industry." Thesis, Georgia Institute of Technology, 1998. http://hdl.handle.net/1853/24107.

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14

王日昇 and Yat-sing Wong. "Production scheduling for virtual cellular manufacturing systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B31239468.

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15

马俊 and Jun Ma. "Dynamic production scheduling in virtual cellular manufacturing systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hdl.handle.net/10722/193066.

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Manufacturing companies must constantly improve productivity to respond to dynamic changes in customer demand in order to maintain their competitiveness and marketshares. This requires manufacturers to adopt more efficient methodologies to design and control their manufacturing systems. In recent decades, virtual cellular manufacturing (VCM), as an advanced manufacturing concept, has attracted increasing attention in the research community, because traditional cellular manufacturing is inadequate when operating in a highly dynamic manufacturing environment. Virtual cellular manufacturing temporarily and dynamically groups production resources to form virtual cells according to production requirements, thus enjoying high production efficiency and flexibility simultaneously. The objective of this research is to develop cost-effective methodologies for manufacturing cell formation and production scheduling in virtual cellular manufacturing systems (VCMSs), operating in single-period/multi-period, and dynamic manufacturing environments. In this research, two mathematical models are developed to describe the characteristics of VCMSs operating under a single-period and a multi-period manufacturing environment respectively. These models aim to develop production schedules to minimize the total manufacturing cost incurred in manufacturing products for the entire planning horizon, taking into consideration many practical constraints such as workforce requirements, effective capacities of production resources, and delivery due dates of orders. In the multi-period case, worker training is also considered and factors affecting worker training are analyzed in detail. This research also develops a novel hybrid algorithm to solve complex production scheduling problems optimally for VCMSs. The hybrid algorithm is based on the techniques of discrete particle swarm optimization, ant colony system and constraint programming. Its framework is discrete particle swarm optimization which can locate good production schedules quickly. To prevent the optimization process being trapped into a local optimum, concepts of ant colony system and constraint programming are incorporated into the framework to greatly enhance the exploration and exploitation of the solution space, thus ensuring better quality production schedules. Sensitivity analyses of the key parameters of the hybrid algorithm are also conducted in detail to provide a theoretical foundation which shows that the developed hybrid algorithm is indeed an excellent optimization tool for production scheduling in VCMSs. In practice, the occurrence of unpredictable events such as breakdown of machines, change in the status of orders and absenteeism of workers will make the current production schedule infeasible. A new feasible production schedule may therefore need to be generated rapidly to ensure smooth manufacturing operations. This research develops several cost-effective production rescheduling strategies for VCMSs operating under different dynamic manufacturing environments. These strategies facilitates the determination of when-to and how-to take rescheduling actions. To further enhance the performance of such strategies in generating new production schedules, especially for large-scale manufacturing systems, a parallel approach is established to implement the developed hybrid algorithm on GPU with compute unified device architecture. The convergence characteristics of the proposed hybrid algorithm are also studied theoretically by using probability theory and Markov chain model. The analysis results show that the optimization process will eventually converge to the global optimal solution.
published_or_final_version
Industrial and Manufacturing Systems Engineering
Doctoral
Doctor of Philosophy

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16

Yang, Fengyu, and 楊丰羽. "Machine-order search space for job-shop scheduling." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B31246205.

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Charnsirisakskul, Kasarin. "Demand fulfillment flexibility in capacitated production planning." Diss., Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/25667.

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18

刑衛國 and Weiguo Xing. "Evaluation and scheduling of private power production." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31242522.

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19

Wan, Sze-yuen, and 溫思源. "Integrated process planning and scheduling with setup time consideration by ant colony optimization." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B49618076.

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In recent years, lots of research effort was spent on the integration of process planning and job-shop scheduling. Various integrated process planning and scheduling (IPPS) models and solution approaches have been proposed. The previous and existing research approaches are able to demonstrate the feasibility of implementing IPPS. However, most of them assumed that setup time is negligible or only part of the processing time. For machined parts, the setup for each operation includes workpiece loading and unloading, tool change, etc. For setup that depends only on the operation to be processed (sequence-independent), it is applicable to adopt the assumption of not considering setup in IPPS. For setup that depends on both the operation to be processed and the immediately preceding operation (sequence-dependent), it is an oversimplification to adopt such assumption. In such cases, the setup time varies with the sequence of the operations. The process plans and schedules constructed under such assumption are not realistic or not even feasible. In actual practice, therefore, the setup time should be separated from the process time in performing the IPPS functions. In this thesis, a new approach is proposed for IPPS problems with setup time consideration for machined parts. Inseparable and sequence-dependent setup requirements are added into the IPPS problems. The setup times are separated from the process times and they vary with the sequence of the operations. IPPS is regarded as NP-hard problem. With the separated consideration of setup times, it becomes even more complicated. An Ant Colony Optimization (ACO) approach is proposed to handle this complicated problem. The system is constructed under a multi-agent system (MAS). AND/OR graph is used to record the set of feasible production procedures and sequences. The ACO algorithm computes results by an autocatalytic process with the objective to minimize the makespan. Software agents called “artificial ants” traverse through the feasible routes in the graph and finally construct a schedule. A setup time parameter is added into the algorithm to influence the ants to select the process with less setup time. The approach is able to construct a feasible solution with less setup time. Experimental studies have been performed to evaluate the performance of MAS-ACO approach in solving IPPS problems with separated consideration of setup times. The experimental results show that the MAS-ACO approach can effectively handle the problem.
published_or_final_version
Industrial and Manufacturing Systems Engineering
Master
Master of Philosophy

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20

Alvfors, Oskar, and Fredrik Björelind. "Optimization of Production Scheduling in the Dairy Industry." Thesis, KTH, Optimeringslära och systemteori, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-170175.

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This thesis presents a case study of mathematical production scheduling optimization applied on Arla Foods AB’s production of dairy products. The scheduling was performed as a possible remedy for problems caused by overcrowded finished goods warehouse. Based on the scheduling, conclusions were made on whether the existing two-shift production is sufficient or if an additional night shift should be introduced. In parallel, an empirical and theoretical analysis on the perceived effects of night shift work on employees was conducted. For the optimization, mixed integer programming was used to model the production context through a discrete time scheduling lot-sizing model developed in this thesis. The model developed and implemented on Arla Foods AB contributes to the research field through its feature of relatively low complexity enabling scheduling of extensive production systems when applied in industrial contexts where products may be categorized. The thesis concludes that mathematical production scheduling can solve Arla Foods AB’s production problematics and suggests reallocation of the existing shifts for the purpose of reduced costs and acceptable warehouse levels. This reallocation would incur production during inconvenient hours whereas management remedies reducing negative effects of night shift work are identified.
Denna avhandling innefattar en studie av matematisk optimering av produktionsscheman applicerad på Arla Foods ABs produktion av mejeriprodukter. Schemaläggningen utfördes som en möjlig lösning på produktionsproblematik orsakad av överfyllda färdigvarulager. Utifrån de optimerade produktionsschemana drogs slutsatser kring om dagens produktionsstruktur på två skift är tillräcklig eller om introduktion av ett andra nattskift skulle vara fördelaktig. Parallellt med detta presenteras en empirisk och teoretisk studie kring de produktionsanställdas uppfattning kring effekter av att arbeta nattskift. För optimeringen har heltalsoptimering (eng: mixed integer programming) använts för modellering av produktionen genom en produktionsplaneringsmodell med diskret tidsrepresentation (eng: discrete time scheduling lot-sizing model ) som utvecklas i denna avhandling. Denna model, som även appliceras på Arla Foods ABs produktion, presenteras i detalj och karaktäriseras av låg komplexitet vilket möjliggör schemaoptimering av omfattande produktionssystem givet att produktportföljen kan kategoriseras i produktgrupper med liknande egenskaper ur ett produktionsperspektiv. Avhandlingen fastslår att matematisk optimering av produktionsscheman har potential att lösa produktionsproblematiken på Arla Foods AB och föreslår en reallokering av den nuvarande produktionen för minskade kostnader och utjämnade nivåer i färdigvarulager. Produktionsomläggningen skulle innebära produktion under obekväm arbetstid vilket föranleder en analys av initiativ som har potential att minska de negativa effekterna av nattskiftarbete för de produktionsanställda.

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21

丘杰 and Jie Qiu. "Scheduling flexible manufacturing systems using fuzzy heuristics." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B31244671.

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22

蘇美子 and Mee-chi Meko So. "An operations research model and algorithm for a production planning application." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B31226681.

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23

Luo, Hao, and 罗浩. "Hybrid flowshop scheduling with job interdependences using evolutionary computing approaches." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B47849551.

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This research deals with production scheduling of manufacturing systems that predominantly consist of hybrid flowshops. Hybrid Flowshop Scheduling (HFS) problems are common in metal working industries. Their solution has significant inferences on company performance in a globally competitive market in terms of production cycle time, delivery dates, warehouse and work-in-process inventory management. HFS problems have attracted considerable research efforts on examining their scientific complexity and practical solution algorithms. In conventional HFS systems, an individual job goes through the flowshop with its own processing route, which has no influence on other jobs. However, in many metal working HFS systems, jobs have interdependent relationships during the process. This thesis focuses on addressing two classes of HFS problems with job interdependence that have been motivated by real-life industrial problems observed from our collaborating companies. The first class of HFS problems with job interdependence are faced by manufacturers of typically standard metal components where jobs are organized in families according to their machine settings and tools. Family setup times arise when a machine shifts from processing one job family to another. This problem is compounded by the challenges that the formation of job families is different in different stages and only a limited number of jobs can be processed within one setup. This class of problems is defined as HFS with family setup and inconsistent family formation. The second class of HFS problems with job interdependence is typically faced in a production process consisting of divergent operations where a single input item is converted into multiple output items. Two important challenges have been investigated. One is that one product can be produced following different process routes. The other is that the total inventory capacity is very limited in the company in the sense that the inventory spaces are commonly shared by raw materials, work-in-process items and finished products. This class of problems is defined as HFS with divergent production and common inventory. The aim is to analyze the general characteristics of HFS with job interdependence and develop effective and practical methodologies that can tackle real-world constraints and reduce the scheduling effort in daily production. This research has made the following contributions: (1) A V-A-X structural classification has been proposed to represent the divergent (V), convergent (A) and mixed (X) job interdependent relations during the production. (2) A genetic algorithm based approach and a particle swarm optimization based approach have been developed to solve two classes of HFS problems with job interdependence, respectively. The computational results based on actual production data have shown that the proposed solutions are robust, efficient and advantageous for solving the practical problems. (3) A waiting factor approach and delay timetable approach have been developed to extend the solutions space of two classes of HFS problems by inserting intentional idle times into original schedules. The computational results have indicated that better schedules can be obtained in the extended solution spaces.
published_or_final_version
Industrial and Manufacturing Systems Engineering
Doctoral
Doctor of Philosophy

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24

Zhao, Ying. "Optimization of cooperative material handling systems." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B37837710.

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25

Wong, Tse-chiu, and 黃資超. "An iterative genetic algorithm-based approach to machine assignment problems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B3035710x.

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26

Luo, Hao, and 羅浩. "Two-stage hyhrid flowshop scheduling in a metalworking company using genetic algorithm." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B41758109.

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27

Higgins, Andrew. "Optimisation of train schedules to minimise transit time and maximise reliability." Thesis, Queensland University of Technology, 1996. https://eprints.qut.edu.au/107082/1/T%28S%29%20118%20Optimisation%20of%20train%20schedules%20to%20minimise%20transit%20time%20and%20maximise%20reliability.pdf.

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The overall performance of a train schedule is measured in terms of the mean and variance of train lateness (reliability) as well as the travel time of individual trains. The concept is a critical performance measure for both urban and non-urban rail passenger services, as well as rail freight transportation. This thesis deals with the scheduling of trains on single track corridors, so as to minimise train trip times and maximise reliability of train arrival times. A method to quantify the amount of risk of delay associated with each train, each track segment, and the schedule as a whole, is put forward and used as the reliability component of the constrained optimisation model. As well as for schedule optimisation, the risk of delay model can be applied to the prioritisation of investment projects designed to improve timetable reliability. Comparisons can be made between track, terminal and rolling stock projects, in terms of their likely impact on timetable reliability. The thesis also describes a number of solution techniques for the scheduling problem. New lower bounds for the branch and bound technique are presented which allow solutions for reasonable size train scheduling problems to be determined efficiently. Three solution heuristic techniques are applied to the train scheduling problem, namely: a local search heuristic with an improved neighbourhood structure; genetic algorithms with an efficient string representation; and tabu search. Comparisons in terms of the number of calculations and solution quality are made between the heuristic and branch and bound techniques. The branch and bound technique with the best lower bound out performed genetic algorithms and tabu search for all except the largest size problems.

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28

Wade, Richard Barry. "Modeling and analysis of scheduling restaurant personnel." Thesis, Virginia Tech, 1993. http://hdl.handle.net/10919/41407.

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29

Vijayvargiya, Mool C. "Developing a mathematical model for scheduling re-layout projects." Ohio : Ohio University, 1994. http://www.ohiolink.edu/etd/view.cgi?ohiou1178737658.

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30

Zhang, Sicheng, and 张思成. "An enhanced ant colony optimization approach for integrating process planning and scheduling based on multi-agent system." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B49618064.

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Process planning and scheduling are two important manufacturing planning functions which are traditionally performed separately and sequentially. Usually, the process plan has to be prepared first before scheduling can be performed. However, due to the complexity of manufacturing systems and the uncertainties and dynamical changes encountered in practical production, process plans and schedules may easily become inefficient or even infeasible. The concept of integrated process planning and scheduling (IPPS) has been proposed to improve the efficiency, effectiveness as well as flexibility of the respective process plan and schedule. By combining both functions together, the process plan for producing a part could be dynamically arranged in accordance with the availability of manufacturing resources and current status of the system, and its operations’ schedule could be determined concurrently. Therefore, IPPS could provide an essential solution to the dynamic process planning and scheduling problem in the practical manufacturing environment. Nevertheless, process planning and scheduling are both complex functions that depend on many factors and flexibilities in the manufacturing system, IPPS is therefore a highly complex NP-hard problem. Ant colony optimization (ACO) is a widely applied meta-heuristics, which has been proved capable of generating feasible solutions for IPPS problem in previous research. However, due to the nature of the ACO algorithm, the performance is not that favourable compared with other heuristics. This thesis presents an enhanced ACO approach for IPPS. The weaknesses and limitations of standard ACO algorithm are identified and corresponding modifications are proposed to deal with the drawbacks and improve the performance of the algorithm. The mechanism is implemented on a specifically designed multi-agent system (MAS) framework in which ants are assigned as software agents to generate solutions. First of all, the manufacturing processes of the parts are graphically formulated as a disjunctive AND/OR graph. In applying the ACO algorithm, ants are deployed to find a path on the disjunctive graph. Such an ant route indicates a corresponding solution with associated operations scheduled by the sequence of ant visit. The ACO in this thesis is enhanced with the novel node selection heuristic and pheromone update strategy. With the node selection heuristic, pheromone is deposited on the nodes as well as edges on the ant path. This is contrast to the conventional ACO algorithm that pheromone is only deposited on edges. In addition, a more reasonable strategy based on “earliest completion time” of operations are used to determine the heuristic desirability of ants, instead of the “greedy” strategy used in standard ACO, which is based on the “shortest processing time”. The approach is evaluated by a comprehensive set of problems with a full set of flexibilities, while multiple performance measurements are considered, including makespan, mean flow time, average machine utilization and CPU time, among which makespan is the major criterion. The results are compared with other approaches and encouraging improvements on solution quality could be observed.
published_or_final_version
Industrial and Manufacturing Systems Engineering
Master
Master of Philosophy

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31

Vance, Pamela H. "Crew scheduling, cutting stock, and column generation : Solving huge integer programs." Diss., Georgia Institute of Technology, 1993. http://hdl.handle.net/1853/23333.

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Yang, Donghai, and 杨东海. "Dynamic planning and scheduling in manufacturing systems with machine learning approaches." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B41757968.

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33

Mardix, Ido. "Throughout efficiency analysis of the mobot-carousel storage system." Thesis, Georgia Institute of Technology, 1985. http://hdl.handle.net/1853/24233.

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34

Bakkalbasi, Omer. "Flow path network design and layout configuration for material delivery systems." Diss., Georgia Institute of Technology, 1989. http://hdl.handle.net/1853/25617.

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35

Zhao, Ying, and 趙穎. "Optimization of cooperative material handling systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B37837710.

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36

Chung, Sai-ho, and 鍾世豪. "A genetic algorithm approach in distributed scheduling in multi-factory production networks." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B37826773.

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Tsang, Wan-sze, and 曾韻詩. "Genetic algorithm for scheduling yard cranes in port container terminals." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B29544609.

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38

Kamat, Kuldip U. "Minimizing total tardiness and crew size in labor intensive cells using mathematical models." Ohio : Ohio University, 2007. http://www.ohiolink.edu/etd/view.cgi?ohiou1181108441.

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39

Ge, Ya, and 戈亞. "Scheduling the landside operations of a container terminal using a fuzzy heuristic." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B37825525.

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40

Leu, Yow-yuh. "Cellular manufacturing: applicability and system design." Diss., Virginia Tech, 1991. http://hdl.handle.net/10919/39922.

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As competition has intensified, many American manufacturers have sought alternatives to rejuvenate their production systems. Cellular manufacturing systems have received considerable interest from both academics and practitioners. This research examines three major issues in cellular manufacturing that have not been adequately addressed: applicability, structural design, and operational design. Applicability, in this study, is concerned with discerning the circumstances in which cellular manufacturing is the system of choice. The methodology employed is simulation and two experimental studies are conducted. The objective of Experiment I, a 2 x 3 x 3 factorial design, is to investigate the role of setup time and move time on system performance and to gain insight into why and how one layout could outperform another. The results of Experiment I suggest that move time is a significant factor for job shops and that workload variation needs to be reduced if the performance of cellular manufacturing is to be improved. Experiment II evaluates the impact of setup time reduction and operational standardization on the performance of cellular manufacturing. The results of Experiment II suggest that cellular manufacturing is preferred if the following conditions exist: (1) well balanced workload, (2) standardized products, (3) standardized operations, and (4) setup times independent from processing times.
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41

Carroll, Robert. "The pure assembly multi-stage production-scheduling problem : a mathematical treatment and the creation of a new algorithm." Thesis, University of Sheffield, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.401135.

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42

Wang, Yinhua. "Fleet assignment, eulerian subtours and extended steiner trees." Diss., Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/24922.

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43

Dillon, Jeffrey Elliot. "The design of fixed routes in local area systems." Thesis, Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/25519.

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44

王曉曦 and Xiaoxi Wang. "Design of virtual cellular manufacturing systems using genetic algorithms." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B42577305.

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45

Khan, Asif [Verfasser], Christian [Akademischer Betreuer] Niemann-Delius, and Marco [Akademischer Betreuer] Lübbecke. "Development of new metaheuristic tools for long term production scheduling of open pit mines / Asif Khan ; Christian Niemann-Delius, Marco Lübbecke." Aachen : Universitätsbibliothek der RWTH Aachen, 2016. http://d-nb.info/1129180808/34.

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46

West-Hansen, Jan. "Long-term scheduling in underground coal mining using mixed binary programming." Diss., Virginia Polytechnic Institute and State University, 1989. http://hdl.handle.net/10919/54807.

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Recognizing the complexity of coal mining management, e.g., the scarcity of financial resources and the high level of uncertainty, a mixed binary programming model has been developed as an aid for generating production schedules which maximize the associated net present value. Defining the mine layout as a precedence network, with the nodes representing mining blocks, a solution procedure is developed, based on Benders' partitioning scheme. That is, the procedure iterates between two problems, namely, the master (primal) problem, solved by a combination of heuristic and exact methods, and the subproblem (dual problem), solved partly by inspection and partly as a minimal cost network flow problem. The heuristic methods are based on improvements of existing algorithms for scheduling precedence-related jobs on m processors. Computational experiences are presented and the procedure is demonstrated on a mining case.
Ph. D.

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47

Harihara, Ramachandra Sharma. "Modeling of Scheduling Algorithms with Alternative Process Plans in an Optimization Programming Language." Ohio University / OhioLINK, 2004. http://www.ohiolink.edu/etd/view.cgi?ohiou1108045192.

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48

Liu, Zhixin. "Capacity allocation and rescheduling in supply chains." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1187883767.

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49

Chen, Chin-Sheng. "Methodologies for manufacturing system selection and for planning and operation of a flexible manufacturing system." Diss., Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/54242.

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A hierarchical methodology is developed for the overall design of manufacturing systems. The methodology consists of solutions to four levels of problems, namely, (1) manufacturing system selection, (2) shop loading, (3) machine loading and tool allocation, and (4) testing the feasibility of a schedule and determining strategies for the operational control of the system. Although these problem levels are developed in a hierarchical sense, they can be applied independently by assuming appropriate inputs to the problem level under consideration. The third and the fourth level problems are addressed in this research for the flexible manufacturing system. The first level of the hierarchical methodology addresses the problem of manufacturing system selection. The mathematical 4 model formulated for this problem captures the basic and integrated relationships among the systems and system components. This model provides a practical approach and a precise tool to determine an optimal mix of systems, to assign appropriate machines to each system, and to select the best material handling system for each system to best suit long-term production requirements at minimum costs. The second level of the hierarchical methodology addresses the shop loading problem. A mathematical model is developed for partitioning parts among the manufacturing systems selected at the first level to minimize total operating costs. For the third level problem, a mathematical model is formulated to obtain routings of parts through an FMS and to assign appropriate cutting tools to each machine in the system to minimize total machining cost. For the fourth level problem, a simulation model is developed for testing the feasibility of the solution obtained at the third level. It also helps to determine strategies for the operational control of the system. The computational experience with the mathematical models is presented using the MPSX-MIP/370 package. Sensitivity analysis is also performed to further understand system behavior under various operating conditions. Several new findings of the research are reported. Because of the special structure of the mathematical models, a computational refinement for their solution is also proposed based on Lagrangian relaxation.
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50

Grobler, Jacomine. "Particle swarm optimization and differential evolution for multi-objective multiple machine scheduling." Diss., Pretoria : [s.n.], 2009. http://upetd.up.ac.za/thesis/available/etd-05062009-164124/.

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