Littérature scientifique sur le sujet « Mixed blocking constraints »

In this paper, we consider a job-shop scheduling problem with mixed blocking constraints. Contrary to most previous studies, where no blocking or only one type of blocking constraint was used among successive operations, we assume that, generally, we may address several different blocking constraints in the same scheduling problem depending on the intermediate storage among machines, the characteristics of the machines, the technical constraints, and even the jobs. Our objective was to schedule a set of jobs to minimize the makespan. Thus, we propose, for the first time, a mathematical model of the job-shop problem taking into account the general case of mixed blocking constraints, and the results were obtained using Mosel Xpress software. Then, after explaining why and how groups of jobs have to be processed, a blocking constraint conflict-free warranted evaluation function is proposed and tested with the particle swarm optimization and genetic algorithm methods. The results prove that we obtained a near-optimal solution to this problem in a very short time.

Permutation flowshop scheduling problem (PFSP) is a classical combinatorial optimisation problem. There exist variants of PFSP to capture different realistic scenarios, but significant modelling gaps still remain with respect to real-world industrial applications such as the cider production line. In this paper, we propose a new PFSP variant that adequately models both overlapable sequence-dependent setup times (SDST) and mixed blocking constraints. We propose a computational model for makespan minimisation of the new PFSP variant and show that the time complexity is NP Hard. We then develop a constraint-guided local search algorithm that uses a new intensifying restart technique along with variable neighbourhood descent and greedy selection. The experimental study indicates that the proposed algorithm, on a set of wellknown benchmark instances, significantly outperforms the state-of-the-art search algorithms for PFSP.

The flow shop scheduling problems with mixed blocking constraints with minimization of makespan are investigated. The Taguchi orthogonal arrays and path relinking along with some efficient local search methods are used to develop a metaheuristic algorithm based on bee colony optimization. In order to compare the performance of the proposed algorithm, two well-known test problems are considered. Computational results show that the presented algorithm has comparative performance with well-known algorithms of the literature, especially for the large sized problems.

An increased use of the high-voltage direct current (HVDC) technologies can have important effects on frequency performance and voltage stability of the receiving-end grid during normal operation as well as during blocking failure. The main reasons are the inherent characteristics of the HVDC such as its much larger capacity than thermal plants and lack of voltage supporting ability to the alternating current (AC) grid. These has led to new challenges for AC/direct current (DC) power grid operators in terms of ensuring power system security. To address these challenges, a unit commitment (UC) of the receiving-end in the AC/DC hybrid grid is presented in this paper. In the proposed model, primary frequency modulation constraints are added to provide sufficient capacity for HVDC blocking. Besides, grid security constraint after secondary frequency regulation is also considered because HVDC blocking failure would cause large range power transfer and transmission lines overload. Meanwhile, voltage stability constraints are employed to guarantee enough voltage supporting capacity from thermal plants at the HVDC feed-in area. Based on the characteristics of the model, Benders decomposition and mixed integer programming algorithm are used to get the optimal transmission power of the HVDC and schedule of thermal units. The study is done by considering the IEEE-39 and Jiangsu power grid in eastern China, containing two HVDC transmission projections respectively. The results are also validated by simulation of different HVDC blocking failure scenarios.

Does young bilingual children's code-mixing obey the same structural constraints as bilingual adults' code-mixing? The present study addresses this question using code-mixing data from 15 French–English bilingual children filmed in conversation with both parents at six-month intervals from the age of 2;0 to 3;6. The children's code-mixed utterances were examined for violations of the principles set out in the Matrix-Language Frame model (e.g. Myers-Scotton, 1993, 1997). The results show that the children obeyed all the constraints set out in the Matrix Language Frame model the majority of the time. With respect to the Morpheme Order Principle and to the interaction of Congruence and Matrix Language Blocking, they demonstrated consistent adherence with only marginal violations from the outset. In contrast, the children produced comparatively more frequent violations of the System Morpheme Principle and showed increasing adherence to this principle over time. We discuss possible explanations for the contrast between the children's performance on the System Morpheme Principle and the other constraints, which include the unequal emergence of INFL in the acquisition of French and English.

As multi-factory production models are more widespread in modern manufacturing systems, a distributed blocking flowshop scheduling problem (DBFSP) is studied in which no buffer between adjacent machines and setup time constraints are considered. To address the above problem, a mixed integer linear programming (MILP) model is first constructed, and its correctness is verified. Then, an iterated greedy-algorithm-blending multi-factory collaboration mechanism (mIG) is presented to optimize the makespan criterion. In the mIG algorithm, a rapid evaluation method is designed to reduce the time complexity, and two different iterative processes are selected by a certain probability. In addition, collaborative interactions between cross-factory and inner-factory are considered to further improve the exploitation and exploration of mIG. Finally, the 270 tests showed that the average makespan and RPI values of mIG are 1.93% and 78.35% better than the five comparison algorithms on average, respectively. Therefore, mIG is more suitable to solve the studied DBFSP_SDST.

Environmental concerns and economic constraints have led to increasing installations of mixed conductor circuits comprising underground cables (UGCs) and overhead transmission lines (OHLs). Faults on the OHL sections of such circuits are usually temporary, while there is a higher probability that faults on UGC sections are permanent. To maintain power system reliability and security, auto-reclose (AR) schemes are typically implemented to minimize outage duration after temporary OHL faults while blocking AR for UGC faults to prevent equipment damage. AR of a hybrid UCG–OHL transmission line, therefore, requires effective identification of the faulty section. However, the different electrical characteristics of UGC and OHL sections present significant challenges to existing protection and fault location methods. This paper presents a selective AR scheme for mixed conductor circuits based on the evaluation of differential currents in multiple defined protection zones, using distributed current transformer (CT) measurements provided by passive optical sensing. Case studies are conducted with a number of different UGC–OHL configurations, and the results demonstrate that the proposed scheme can accurately identify the faulty section, enabling effective selective AR of a comprehensive range of mixed conductor circuit topologies. The proposed scheme is also more cost effective, with reduced hardware requirements compared to conventional solutions. This paper thereby validates the optimal solution for mixed circuit protection as described in CIGRE Working Group B5.23 report 587.

La transformation numérique que vit l’entreprise aujourd’hui a définitivement changé le comportement des consommateurs. En effet, via les nouveaux outils d’information et de communication, un client peut désormais à tout moment créer, modifier ou annuler une commande. Ces évènements fortuits ont un impact sur l’organisation au sein des unités de production. Ils engendrent une perturbation de l’ordonnancement planifié. Par conséquent, un processus de réordonnancement est nécessaire pour réviser efficacement le planning déjà établi, de préférence avec le moins de modifications possibles. Cette thèse propose des modèles mathématiques et des méthodes d’optimisation pour résoudre des problèmes de réordonnancement, afin de parer des perturbations dans des environnements machines différents, et évaluer la performance des solutions obtenues, grâce à un critère combinant l’efficacité et la stabilité de l’ordonnancement. La stratégie prédictive-réactive a été adoptée dans cette étude. Elle consiste, dans la phase prédictive, à résoudre un problème d’ordonnancement classique ayant comme objectif de minimiser la somme des temps d’attente des jobs pondérés par leurs poids, représentant le critère d’efficacité. Dès l’apparition d’une perturbation, vient ensuite la phase réactive, qui consiste à mettre à jour le problème initial en modifiant ses données, puis à résoudre le nouveau problème de réordonnancement, ayant cette fois comme objectif de minimiser le critère d’efficacité décrit auparavant, combiné avec le critère de stabilité. Ce dernier est défini par la somme des différences entre les dates de fin des jobs avant et après l’apparition de la perturbation, pondérées par le poids des jobs. Cette combinaison des deux critères est significative, et peut être très utile dans des applications industrielles, où le temps d’attente des jobs représente le temps d’attente des produits devant le poste de travail, tandis que les poids des jobs représentent l’importance des clients. La mesure de stabilité permet de limiter la déviation par rapport au planning déjà établi, car celle-ci engendre des coûts supplémentaires. Cette approche a été appliquée à différents environnements de machines, en commençant par une machine unique, représentant un seul poste de travail. Puis, sur des machines parallèles, représentant des postes de travail identiques. Et enfin, dans un atelier de type Flowshop, où l’ensemble des jobs doivent passer sur un ensemble de machines dans le même ordre. Ce dernier cas a aussi été étudié en considérant des contraintes de blocage mixtes entre les machines. Ces différents problèmes de réordonnancement ont été modélisés en premier lieu sous forme de modèles mathématiques, adaptés à une Programmation Linéaire en Nombres Entiers (PLNE). Cependant, leur complexité NP-difficile n’a permis leur résolution que pour un nombre limité de jobs. Par conséquent, des méthodes heuristiques ont été développées, permettant de parcourir plus de jobs en un temps raisonnable. La performance des méthodes développées a été discutée et analysée, à la fois en termes de qualité de solution et de temps de calcul
Today’s digital transformation has definitely changed the customers practices. In fact, through the new information and communication tools, a customer can at any time create, modify, or cancel an order. These unexpected events have a direct impact on the work organization of the production unit, generating a disruption of the already established schedule. Therefore, a rescheduling process is necessary for efficiently revising the existing schedule, preferably with less movements. In this Ph.D, mathematical models and optimization methods are developed for rescheduling problems, under different types of disruptions, in several machine environments. The performance of the obtained solutions is measured with a new criterion, simultaneously combining the schedule efficiency and stability.The predictive-reactive scheduling strategy has been adopted in this work. It consists, in the predictive phase, to solve a classical scheduling problem minimizing the Total Weighted Waiting Time (TWWT) of the jobs, regarded as the schedule efficiency criterion. After the disruption appearance, the reactive phase starts. It consists in updating the initial problem by modifying its data, then solving the new rescheduling problem with the objective of minimizing the TWWT combined with a stability criterion. The schedule stability is measured with the Total Weighted Completion Time Deviation (TWCTD). This association of criteria is significant, and it can be very helpful in industrial applications, where the job waiting time estimates the duration that the job has waited in front of a workstation. The stability criterion is then used for limiting the deviation from the already established schedule, since this matter generates supplementary costs.This approach has been applied for different machine environments. Firstly, on a single machine, illustrating the case of a single workstation. Secondly, on parallel machines, describing the case of identical workstations. Finally, on a flowshop system where a set of jobs are treated in the same order by a set of machines. The flowshop rescheduling problem is also considered with mixed blocking constraints.These rescheduling problems have firstly been modeled as Mixed Integer Linear Programing (MILP) models. Due to their NP-hard complexity, the resolution is only possible for a limited number of jobs. Thus, heuristic methods have been designed, exploring more jobs in a reasonable time. The proposed methods have been discussed and analyzed, both in terms of solution quality and computing time

Mixed-grid optical networks are in a migration state where fixed-grid and flex-grid optical networks coexist. To carry point-to-multipoint (P2MP) services in mixed-grid optical networks, routing and resource allocation (RRA) problems need to be solved. Once the RRA fails, services will be blocked and then influence quality of service. The minimized spectrum for satisfying the bandwidth request of services is called as a frequency block (FB). For a service, the total number of available FBs embodies the spectrum availability on a link. Because the fixed-grid and flex-grid links have different channel spacing, spectrum availability on fixed-grid and flex-grid links needs different evaluation method. We propose a RRA algorithm in mixed-grid optical networks for P2MP services by being aware of spectrum availability. The spectrum availability is evaluated according to fixed-grid and flex-grid constraints. Our proposed algorithm achieves the lower blocking probability (BP) than that of benchmark RRA algorithms according to simulation results.