Strategies for scheduling jobs in an identical parallel machine production environment

CAPESCNP

Review on unrelated parallel machine scheduling problem with additional resources

This study deals with an unrelated parallel machine scheduling problem with additional resources (UPMR). That is one of the important sub-problems in the scheduling. UPMR consists of scheduling a set of jobs on unrelated machines. In addition to that, a number of one or more additional resources are needed. UPMR is very important and its importance comes from the wealth of applications; they are applicable to engineering and scientific situations and manufacturing systems such as industrial robots, nurses, machine operators, bus drivers, tools, assembly plant machines, fixtures, pallets, electricity, mechanics, dies, automated guided vehicles, fuel, and more. The importance also comes from the concern about the limitation of resources that are dedicated for the production process. Therefore, researchers and decision makers are still working on UPMR problem to get an optimum schedule for all instances which have not been obtained to this day. The optimum schedule is able to increase the profits and decrease the costs whilst satisfying the customers’ needs. This research aims to review and discuss studies related to unrelated parallel machines and additional resources. Overall, the review demonstrates the criticality of resolving the UPMR problem. Metaheuristic techniques exhibit significant effectiveness in generating results and surpassing other algorithms. Nevertheless, continued improvement is essential to satisfy the evolving requirements of UPMR, which are subject to operational changes based on customer demand

Parallel machine scheduling subject to machine availability constraints

Cataloged from PDF version of article.Within a planning horizon, machines may become unavailable due to unexpected breakdowns or pre-scheduled activities. A realistic approach in constructing the production schedule should explicitly take into account such periods of unavailability. This study addresses the parallel machine-scheduling problem subject to availability constraints on each machine. The objectives of minimizing the total completion time and minimizing the maximum completion time are studied. The problems with both objectives are known to be NP-hard. We develop an exact branch-and-bound procedure and propose three heuristic algorithms for the total completion time problem. Similarly, we propose exact and approximation algorithms also for the maximum completion time problem. All proposed algorithms are tested through extensive computational experimentation, and several insights are provided based on computational results.Sevindik, KayaM.S

A Bicriteria Simulated Annealing Algorithm for Scheduling Jobs on Parallel Machines with Sequence Dependent Setup Times

The study considers the scheduling problem of identical parallel machines subject to minimization of the maximum completion time and the maximum tardiness expressed in a linear convex objective function. The maximum completion time or makespan is the date when the last job to be completed leaves the system. The maximum tardiness is indicated by the job that is completed with the longest delay relative its due date. Minimizing both criteria can help assuring a high utilization of the production system as well as a high level of service towards the client. Due to the complexity of the problem, a Simulated Annealing (SA) heuristic has been implemented to be able to obtain an efficient solution in a reasonable running time. A set of n jobs is assigned, to one of the m identical parallel machines. Each job is processed in only one operation before its completion after which it leaves the system. Constraints, such as due dates for each job and setup times for the machines, are considered. The resolution procedure consists of two phases and begins with an initial solution generator. Then a SA heuristic is applied for further improvement of the solution. 4 generators are used to create an initial solution and 3 to generate neighbour solutions. To test and verify the performance of the proposed resolution procedure, a computational experimentation has been realized on a set of test problems generated ad-hoc

Ordonnancement des opérations dans une unité d'extrusion

Les travaux de ce mémoire traitent du problème d’ordonnancement et d’optimisation de la production dans un environnement de plusieurs machines en présence de contraintes sur les ressources matérielles dans une usine d’extrusion plastique. La minimisation de la somme pondérée des retards est le critère économique autour duquel s’articule cette étude car il représente un critère très important pour le respect des délais. Dans ce mémoire, nous proposons une approche exacte via une formulation mathématique capable des donner des solutions optimales et une approche heuristique qui repose sur deux méthodes de construction de solution sérielle et parallèle et un ensemble de méthodes de recherche dans le voisinage (recuit-simulé, recherche avec tabous, GRASP et algorithme génétique) avec cinq variantes de voisinages. Pour être en totale conformité avec la réalité de l’industrie du plastique, nous avons pris en considération certaines caractéristiques très fréquentes telles que les temps de changement d’outils sur les machines lorsqu’un ordre de fabrication succède à un autre sur une machine donnée. La disponibilité des extrudeuses et des matrices d’extrusion représente le goulot d’étranglement dans ce problème d’ordonnancement. Des séries d’expérimentations basées sur des problèmes tests ont été effectuées pour évaluer la qualité de la solution obtenue avec les différents algorithmes proposés. L’analyse des résultats a démontré que les méthodes de construction de solution ne sont pas suffisantes pour assurer de bons résultats et que les méthodes de recherche dans le voisinage donnent des solutions de très bonne qualité. Le choix du voisinage est important pour raffiner la qualité de la solution obtenue. Mots-clés : ordonnancement, optimisation, extrusion, formulation mathématique, heuristique, recuit-simulé, recherche avec tabous, GRASP, algorithme génétiqueThe thesis deals with the optimization of the production on a number of machines subject to limited availability of the resources in an extrusion facility. Because of its importance to meet deadlines, the objective is to minimize the sum of weighted tardiness. This work presents a linear formulation of the problem and a number of heuristic solution methods. The proposed heuristic solution methods can be divided into two main groups: construction methods and neighborhood search methods. Also solution construction methods are divided in two sub-groups: parallel construction heuristics and serial construction heuristics. Adaptations of the simulated annealing algorithm (SA), the genetic algorithm (GA), the Tabu search (TS) method and the Greedy randomized adaptive search procedure (GRASP) are developed. Five neighborhood structures are used within the four tested neighborhood search algorithms. In our problem, setup times are sequence dependent. Also, extruders and dies are the bottleneck piece of equipment in this industrial setting. Several problem instances were generated for the evaluation of heuristic scheduling algorithms. The experimental study shows that the construction heuristics are not sufficient to ensure good results, however the proposed neighborhood search methods perform very well. Also, the structure of neighborhoods plays an important role to guarantee better results. Keywords: scheduling, optimization, extrusion, mathematical formulation, heuristic, simulated-annealing, tabu-search, GRASP, genetic algorith

A Bicriteria Simulated Annealing Algorithm for Scheduling Jobs on Parallel Machines with Sequence Dependent Setup Times

The study considers the scheduling problem of identical parallel machines subject to minimization of the maximum completion time and the maximum tardiness expressed in a linear convex objective function. The maximum completion time or makespan is the date when the last job to be completed leaves the system. The maximum tardiness is indicated by the job that is completed with the longest delay relative its due date. Minimizing both criteria can help assuring a high utilization of the production system as well as a high level of service towards the client. Due to the complexity of the problem, a Simulated Annealing (SA) heuristic has been implemented to be able to obtain an efficient solution in a reasonable running time. A set of n jobs is assigned, to one of the m identical parallel machines. Each job is processed in only one operation before its completion after which it leaves the system. Constraints, such as due dates for each job and setup times for the machines, are considered. The resolution procedure consists of two phases and begins with an initial solution generator. Then a SA heuristic is applied for further improvement of the solution. 4 generators are used to create an initial solution and 3 to generate neighbour solutions. To test and verify the performance of the proposed resolution procedure, a computational experimentation has been realized on a set of test problems generated ad-hoc

Nuevos algoritmos para el problema de secuenciación en máquinas paralelas no relacionadas y generalizaciones

Para iniciar esta Tesis Doctoral se buscó un problema de producción sencillo pero de amplia aplicación práctica que permitiera adaptarlo para llegar a problemas más generales y de más amplia aplicación. Por este motivo, nos centramos en las máquinas paralelas, y dentro de ellas, en las no relacionadas dado que son una generalización de los casos de máquinas idénticas y de las uniformemente relacionadas. Escogimos el objetivo de minimizar el tiempo máximo de finalización o Cm ax, uno de los más comunes de la literatura. Este problema tiene la facultad de que, a pesar de su carácter teórico, tiene una amplia aplicación práctica, como el caso de secuenciar las tareas de los hornos de cocción cerámicos. Por otra parte se quería ampliar el problema para el caso en que no se usaran todas las máquinas o no se hicieran todos los trabajos necesariamente. Las metas perseguidas son el presentar unos algoritmos sencillos y potentes para la resolución del problema R//Cm ax, capaces de constituirse en el estado del arte. Dado que los modernos ordenadores montan casi en su totalidad varios núcleos en su CPU y los algoritmos se van adaptando a este hecho, también se ha buscado realizar una adaptación de los algoritmos para su uso en paralelo. Finalmente, se pone como meta el encontrar métodos eficaces y sencillos para la resolución de problemas de este tipo en donde no se emplearan todas las máquinas o no se realizaran todos los trabajos. En la presente Tesis Doctoral se realizó un amplio estudio de la literatura existente respecto al problema de máquinas paralelas no relacionadas y se extrajo el estado del arte, así como un estudio del posible tipo de instancias a emplear, dado que no existía una grupo de instancias tipo para este problema. Se presentan cuatro algoritmos iniciales sencillos que mejoran los resultados del estado del arte en algunos casos y dan mejores resultados de media en el conjunto total de instancias tratadas.Fanjul Peyró, L. (2011). Nuevos algoritmos para el problema de secuenciación en máquinas paralelas no relacionadas y generalizaciones [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/9312Palanci