Solving no-wait two-stage flexible flow shop scheduling problem with unrelated parallel machines and rework time by the adjusted discrete Multi Objective Invasive Weed Optimization and fuzzy dominance approach

Purpose: Adjusted discrete Multi-Objective Invasive Weed Optimization (DMOIWO) algorithm, which uses fuzzy dominant approach for ordering, has been proposed to solve No-wait two-stage flexible flow shop scheduling problem. Design/methodology/approach: No-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times and probable rework in both stations, different ready times for all jobs and rework times for both stations as well as unrelated parallel machines with regards to the simultaneous minimization of maximum job completion time and average latency functions have been investigated in a multi-objective manner. In this study, the parameter setting has been carried out using Taguchi Method based on the quality indicator for beater performance of the algorithm. Findings: The results of this algorithm have been compared with those of conventional, multi-objective algorithms to show the better performance of the proposed algorithm. The results clearly indicated the greater performance of the proposed algorithm. Originality/value: This study provides an efficient method for solving multi objective no-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times, probable rework in both stations, different ready times for all jobs, rework times for both stations and unrelated parallel machines which are the real constraints.Peer Reviewe

An Enhanced Discrete Artificial Bee Colony Algorithm to Minimize the Total Flow Time in Permutation Flow Shop Scheduling with Limited Buffers

This paper presents an enhanced discrete artificial bee colony algorithm for minimizing the total flow time in the flow shop scheduling problem with buffer capacity. First, the solution in the algorithm is represented as discrete job permutation to directly convert to active schedule. Then, we present a simple and effective scheme called best insertion for the employed bee and onlooker bee and introduce a combined local search exploring both insertion and swap neighborhood. To validate the performance of the presented algorithm, a computational campaign is carried out on the Taillard benchmark instances, and computations and comparisons show that the proposed algorithm is not only capable of solving the benchmark set better than the existing discrete differential evolution algorithm and iterated greedy algorithm, but also capable of performing better than two recently proposed discrete artificial bee colony algorithms

An Enhanced Discrete Artificial Bee Colony Algorithm to Minimize the Total Flow Time in Permutation Flow Shop Scheduling with Limited Buffers

This paper presents an enhanced discrete artificial bee colony algorithm for minimizing the total flow time in the flow shop scheduling problem with buffer capacity. First, the solution in the algorithm is represented as discrete job permutation to directly convert to active schedule. Then, we present a simple and effective scheme called best insertion for the employed bee and onlooker bee and introduce a combined local search exploring both insertion and swap neighborhood. To validate the performance of the presented algorithm, a computational campaign is carried out on the Taillard benchmark instances, and computations and comparisons show that the proposed algorithm is not only capable of solving the benchmark set better than the existing discrete differential evolution algorithm and iterated greedy algorithm, but also capable of performing better than two recently proposed discrete artificial bee colony algorithms

Ordonnancement des systèmes de production flexibles soumis à différents types de contraintes de blocage

This thesis deals mainly with makespan minimization in Flow-Shop and hybrid Flow-Shop scheduling problems where mixed blocking constraints are considered. In Flow-Shop scheduling problem, a set of N jobs must be executed on a set of M machines. All jobs require the same operation order that must be executed according to the same manufacturing process. Each machine can only execute one job at any time. Pre-emptive operation is not authorized in presented work. In case of hybrid Flow-Shop, at any processing stage k, there exist one or more identical machines Mk. Objective function consists in determining best schedule in order to reduce makespan, i.e. time where all operations are completed.The most common scheduling problem is classical flowshop where buffer space capacity between machines is considered as unlimited. Other problems are characterized by the fact that the storage capacity is limited or null and which generates one blocking constraint. This constraint can be a classical blocking (RSb) or particular blocking (RCb or RCb*). In our works, we present a general case which can be derived from industry and modeled as Flow-Shop and hybrid Flow-Shop systems subject simultaneously to different blocking.To solve these problems, we studied in this thesis complexity of these systems and we proposed exact methods, approached methods and lower bounds.Ce sujet de thèse concerne de manière générale l'évaluation des performances et l'ordonnancement dans des systèmes de production flexibles et principalement les problèmes d'ordonnancement d'atelier de type Flow-Shop et Flow-Shop hybride. Le problème d'ordonnancement d'un Flow-Shop peut être défini ainsi : un ensemble de N jobs composés chacun de M opérations, doivent passer sur M machines dans le même ordre. Une machine peut exécuter une seule opération à la fois, chaque job ne peut avoir qu'une seule opération en cours de réalisation simultanément et la préemption n'est pas autorisée. Dans le cas des Flow-Shops hybrides, Mk machines identiques sont disponibles à chaque étage k en un ou plusieurs exemplaires. Pour cette étude, notre objectif est toujours de minimiser le temps total d'exécution aussi appelé makespan.Les problèmes d'ordonnancement les plus répandus sont de type Flow-Shop classique où les espaces de stockage entre les machines sont considérées comme infinies. D’autres problèmes sont caractérisés par des capacités de stockage limitées ou nulles qui engendre une seule contrainte de blocage. Cette contrainte peut être un blocage classique (de type RSb) ou particulier (de type RCb ou RCb*). Dans nos travaux de recherche, nous présentons un cas général qui peut être tiré de l'industrie et modélisé sous forme de systèmes de type Flow-Shop et Flow-Shop hybride soumis simultanément à plusieurs types de blocage. Pour résoudre ce genre de problèmes, nous avons étudié dans cette thèse la complexité de ces systèmes et nous avons proposé des méthodes exactes, des méthodes approchées ainsi que des bornes inférieures

Production Scheduling

Generally speaking, scheduling is the procedure of mapping a set of tasks or jobs (studied objects) to a set of target resources efficiently. More specifically, as a part of a larger planning and scheduling process, production scheduling is essential for the proper functioning of a manufacturing enterprise. This book presents ten chapters divided into five sections. Section 1 discusses rescheduling strategies, policies, and methods for production scheduling. Section 2 presents two chapters about flow shop scheduling. Section 3 describes heuristic and metaheuristic methods for treating the scheduling problem in an efficient manner. In addition, two test cases are presented in Section 4. The first uses simulation, while the second shows a real implementation of a production scheduling system. Finally, Section 5 presents some modeling strategies for building production scheduling systems. This book will be of interest to those working in the decision-making branches of production, in various operational research areas, as well as computational methods design. People from a diverse background ranging from academia and research to those working in industry, can take advantage of this volume

Hybrid flow-shop scheduling with different constraints: Heuristic solutions and lp-based lower bounds

Während der Herstellung von Stahl ist es erforderlich, kontinuierlich dessen Qualität zu überwachen. Aus diesem Grund werden an verschiedenen Positionen in einem Stahlwerk fortlaufend Produktproben entnommen und analysiert. Ein großer deutscher Stahlerzeuger betreibt zu diesem Zweck ein vollautomatisiertes Labor. Die Proben werden per Rohrpost in dieses Labor gesendet und dort mit Hilfe verschiedener Maschinen untersucht. Notwendige Transporte zwischen diesen Maschinen werden unter Verwendung mehrerer Roboter durchgeführt. Die Belegungsplanung der Maschinen sowie das entsprechende Routing der Roboter bilden ein komplexes Scheduling-Problem. Dabei soll eine möglichst geringe Aufenthaltsdauer der Proben im Labor realisiert werden. Insgesamt kann diese Aufgabe als dynamisches Hybrid Flow-Shop-Problem mit Transporten und Minimierung der gewichteten Gesamtfertigstellungszeit (resp. gewichtete Gesamtflusszeit) klassifiziert werden, da die Ankunftszeit der Proben a priori nicht bekannt ist. Weil die Analyse einer Probe im Labor zudem maximal wenige Minuten dauern darf, steht nur eine sehr geringe Rechenzeit zur Lösung dieses Scheduling-Problems zur Verfügung. Die Entwicklung eines neuen Entscheidungssystems zur Optimierung der Arbeitsabläufe in einem solchen Labor ist ein Bestandteil der vorliegenden Dissertation. Dazu wird ein mehrstufiges heuristisches Lösungsverfahren entwickelt, welches auf einem Dekompositionsansatz, (engpass-orientierten) Prioritätsregeln und einer job-orientierten List Scheduling Strategie basiert. Die Arbeitsweise des Verfahrens für das Labor wird im Rahmen einer Fallstudie simuliert und die erzielten Lösungen mit dem Ist-Zustand des Labors verglichen. In der entsprechenden Analyse kann ein enormes Verbesserungspotential gegenüber dem derzeit verwendeten Planungstool nachgewiesen werden. Neben diesem anwendungsorientierten Teil der Arbeit wird die Performance des vorgestellten Verfahrens auch für allgemeinere Situationen empirisch untersucht. Zur Auswertung der erzielten Lösungen für verschiedene zufällig generierte Datensätze (insgesamt 1500 Probleminstanzen), werden zwei LP-basierte untere Schranken verwendet, welche auf einer zeit-indizierten gemischt-ganzzahligen Modellierung des Problems beruhen. Darüber hinaus werden diese Schranken auch auf theoretischer Ebene analysiert und mit weiteren in der Literatur gebräuchlichen Schranken verglichen.During the manufacture of steel, its quality has to be monitored continuously. Therefore, samples are taken at several stages of the production process and their chemical composition is analyzed. A big German steel producer uses an automatic laboratory to perform this task. The samples are sent to this laboratory under usage of a pneumatic post system and afterwards they are processed by different machines. Arising transportation tasks between those operations are managed by a fleet of robots. The imetabling of the several machines as well as the related routing of the robots is a complex scheduling problem. Therein the flow time of the samples should be minimized. Altogether, this task can be classified as a dynamic hybrid flow-shop scheduling problem with transportation and total weighted completion time or total weighted flow time objective, because the arrival times of the samples are not known in advance. Because the analysis of one sample should at most last a few minutes, the available computational time to perform the required real-time optimization is strictly limited. The development of a decision support system to optimize the workflow in such a laboratory is one part of this dissertation. Therefore, a multi-stage heuristic algorithm is designed, which is based on a decomposition approach, (bottleneck related) dispatching rules as well as a job-oriented list scheduling strategy. The performance of this method in case of the laboratory is simulated and compared to the current control system. It can be shown that the new approach is able to reduce the total weighted flow time significantly. Beneath this application part of the thesis, the performance of the method is further evaluated in a more theoretical fashion. Therefore, an extensive empirical analysis is performed, where lower bounds are used to benchmark the heuristic solutions to 1500 random problem instances under consideration. These bounds are based on the lp relaxation of two time-indexed mixed-integer formulations of the problem. Furthermore, they are also compared to different other bounds introduced in literature