A fast heuristic for a lot splitting and scheduling problem of a textile industry

In this paper we address a lot splitting and scheduling problem of a Textile factory that produces garment pieces. Each garment piece is made of a set of components that are produced on the knitting section of the company. The problem consists of finding a weekly production plan for the knitting section, establishing the quantities to produce of each component (organized in one or several lots), and where and when starting/completion times) to produce them. The main contribution of this work is the development of a constructive heuristic that generates automated knitting scheduling plans. The heuristic produces solutions very fast for a set of randomly generated instances based on real world data

Parallel machine scheduling with precedence constraints and setup times

This paper presents different methods for solving parallel machine scheduling problems with precedence constraints and setup times between the jobs. Limited discrepancy search methods mixed with local search principles, dominance conditions and specific lower bounds are proposed. The proposed methods are evaluated on a set of randomly generated instances and compared with previous results from the literature and those obtained with an efficient commercial solver. We conclude that our propositions are quite competitive and our results even outperform other approaches in most cases

Multiobjective Order Acceptance and Scheduling on Unrelated Parallel Machines with Machine Eligibility Constraints

This paper studies the order acceptance and scheduling problem on unrelated parallel machines with machine eligibility constraints. Two objectives are considered to maximize total net profit and minimize the makespan, and the mathematical model of this problem is formulated as multiobjective mixed integer linear programming. Some properties with respect to the objectives are analysed, and then a classic list scheduling (LS) rule named the first available machine rule is extended, and three new LS rules are presented, which focus on the maximization of the net profit, the minimization of the makespan, and the trade-off between the two objectives, respectively. Furthermore, a list-scheduling-based multiobjective parthenogenetic algorithm (LS-MPGA) is presented with parthenogenetic operators and Pareto-ranking and selection method. Computational experiments on randomly generated instances are carried out to assess the effectiveness and efficiency of the four LS rules under the framework of LS-MPGA and discuss their application environments. Results demonstrate that the performance of the LS-MPGA developed for trade-off is superior to the other three algorithms

Schedule generation schemes for the job-shop problem with sequence-dependent setup times: dominance properties and computational analysis

We consider the job-shop problem with sequence-dependent setup times. We focus on the formal definition of schedule generation schemes (SGSs) based on the semi-active, active, and non-delay schedule categories. We study dominance properties of the sets of schedules obtainable with each SGS. We show how the proposed SGSs can be used within single-pass and multi-pass priority rule based heuristics. We study several priority rules for the problem and provide a comparative computational analysis of the different SGSs on sets of instances taken from the literature. The proposed SGSs significantly improve previously best-known results on a set of hard benchmark instances

A survey of scheduling problems with setup times or costs

Author name used in this publication: C. T. NgAuthor name used in this publication: T. C. E. Cheng2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Heurística de programação da produção para uma indústria cerâmica

Mestrado em Engenharia e Gestão IndustrialAtualmente, uma organização industrial com vista a singrar no mercado global é fortemente influenciada por pressões que visam o aumento da eficiência global e consequente redução de custos operacionais. O desafio para as mesmas passa, portanto, por expurgar do produto tudo aquilo que não lhe acrescenta valor percetível pelo cliente e por maximizar a utilização dos vários recursos industriais instalados. No seguimento deste desafio, surge o Problema de Planeamento e Programação da Produção, ao qual é necessário dar uma resposta eficiente. Este projeto tem como objetivo estudar o problema da Programação da Produção numa indústria de pavimentos e revestimentos cerâmicos, desenvolvendo uma heurística construtiva capaz de traduzir com fiabilidade a realidade do processo produtivo da mesma e, se possível, auxiliar na sua resolução. O problema da programação da produção em estudo visa responder às questões: o quê, em que quantidade, quando e em que linha produzir, por forma a satisfazer as necessidades dos clientes num prazo previamente estipulado como admissível, garantindo o enchimento dos fornos ligados. Sem grandes constrangimentos ao normal lavor da Produção, pretende obter-se com a heurística planos de produção viáveis, que minimizem o tempo necessário para a conclusão do conjunto de referências com necessidades produtivas. O problema é também abordado através de um modelo exato como um problema de máquinas paralelas idênticas capacitado, com matriz de compatibilidades, setups de família e de subfamília e com lotes mínimos de produção. Quer a heurística quer o modelo de programação inteira mista desenvolvidos permitem obter planos de produção válidos, equivalentes aos obtidos atualmente pela empresa através dos meios de programação atuais, embora com um dispêndio de tempo muito inferior.Currently, an industrial organization in order to succeed in the global market is strongly influenced by pressures aimed at increasing the overall efficiency and reducing of their operating costs. The challenge for them is, therefore, to purge all that does not add discernible value to the product in perception of the customer and maximize utilization of the installed industrial resources. Following this challenge, there is the problem of Production Planning and Scheduling, which demands an effectively response. This project aims to study the problem of Production Scheduling in the flooring and ceramic tiles industry, developing a constructive heuristic able to reliably translate the reality of the production process and, if possible, assist in it's resolution. The problem of production scheduling in study aims to answer the questions: what, in what quantity, when and on which line to produce in order to meet customer needs within a previously stipulated acceptable time, ensuring the filling of connected furnaces. With no major constraints to the normal work flow, the heuristic aims to obtain viable production plans that minimize the production time required to complete the set of products needed. The problem is also addressed with an exact method as a problem of parallel identical capable machines, with compatibility matrix, with family and subfamily setups, and with minimum production batch sizes. Both the heuristic and the MIP model developed allows obtaining valid production plans, currently equivalent to those obtained currently by the company through the current programming means, although with a much lower time expenditure

The dynamic, resource-constrained shortest path problem on an acyclic graph with application in column generation and literature review on sequence-dependent scheduling

This dissertation discusses two independent topics: a resource-constrained shortest-path problem (RCSP) and a literature review on scheduling problems involving sequence-dependent setup (SDS) times (costs). RCSP is often used as a subproblem in column generation because it can be used to solve many practical problems. This dissertation studies RCSP with multiple resource constraints on an acyclic graph, because many applications involve this configuration, especially in column genetation formulations. In particular, this research focuses on a dynamic RCSP since, as a subproblem in column generation, objective function coefficients are updated using new values of dual variables at each iteration. This dissertation proposes a pseudo-polynomial solution method for solving the dynamic RCSP by exploiting the special structure of an acyclic graph with the goal of effectively reoptimizing RCSP in the context of column generation. This method uses a one-time âÂÂpreliminaryâ phase to transform RCSP into an unconstrained shortest path problem (SPP) and then solves the resulting SPP after new values of dual variables are used to update objective function coefficients (i.e., reduced costs) at each iteration. Network reduction techniques are considered to remove some nodes and/or arcs permanently in the preliminary phase. Specified techniques are explored to reoptimize when only several coefficients change and for dealing with forbidden and prescribed arcs in the context of a column generation/branch-and-bound approach. As a benchmark method, a label-setting algorithm is also proposed. Computational tests are designed to show the effectiveness of the proposed algorithms and procedures. This dissertation also gives a literature review related to the class of scheduling problems that involve SDS times (costs), an important consideration in many practical applications. It focuses on papers published within the last decade, addressing a variety of machine configurations - single machine, parallel machine, flow shop, and job shop - reviewing both optimizing and heuristic solution methods in each category. Since lot-sizing is so intimately related to scheduling, this dissertation reviews work that integrates these issues in relationship to each configuration. This dissertation provides a perspective of this line of research, gives conclusions, and discusses fertile research opportunities posed by this class of scheduling problems. since, as a subproblem in column generation, objective function coefficients are updated using new values of dual variables at each iteration. This dissertation proposes a pseudo-polynomial solution method for solving the dynamic RCSP by exploiting the special structure of an acyclic graph with the goal of effectively reoptimizing RCSP in the context of column generation. This method uses a one-tim

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

Une approche interdisciplinaire pour l'ordonnancement des transports

Dans cette thèse, nous proposons d’aborder l’ordonnancement des transports par une approche interdisciplinaire. L’idée est d’intégrer les facteurs humains dans le système d’aide à la décision réalisé, de façon à ce que l’homme puisse agir sur la modélisation et la résolution du problème. Le système proposé doit offrir de la flexibilité, afin d’être capable de s’adapter aux nouvelles situations et aux changements, même si ceux-ci n’ont pas été prévus initialement par le concepteur du système. Pour atteindre l’objectif fixé, nous nous sommes notamment appuyé sur une analyse du domaine de travail (« Work Domain Analysis ») basée sur une hiérarchie d’abstraction des entités (physiques ou plus abstraites) manipulées dans ce type de problèmes. Nous avons proposé une architecture pour le système d’aide à la décision basée sur cette analyse du domaine et la programmation par contraintes. Nous avons également conçu, et intégré dans le système, des algorithmes dédiés et des méthodes de résolution basés sur le principe d’inversion de modèle. Enfin, nous avons proposé une architecture d’interfaces avec l’objectif d’assister efficacement l’opérateur humain dans la réalisation des différentes sous-tâches nécessaires à la résolution globale du problème. L’étude du sujet interdisciplinaire a été précédée d’une analyse focalisée sur la résolution de problèmes théoriques d’ordonnancement à machines parallèles avec contraintes de précédence et temps de préparation des machines entre opérations, utilisant des méthodes de recherche arborescente basée sur les divergences.An interdisciplinary approach has been proposed for the vehicle routing problem. The idea is to consider human factors and dynamic aspects for the decision support system (DSS) design. In our approach, a link is done between methods of operations research and an ecological interface design coming from engineering cognitive. A work domain analysis for the vehicle routing problem has been done. The analysis is realized through an abstraction hierarchy, which facilitates the identification of the problem constraints. We have proposed a DSS architecture based on this analysis and on constraint programming. Specific algorithms and solving mechanisms based on model inversion have been proposed and integrated in the system. Finally, we have design a set of human-machine interfaces in order to facilitate the problem solving to the human planning. The interdisciplinary study has been preceded by an analysis of the parallel machine scheduling problem with precedence constraints and setup times. Tree searches and local searches based on limited discrepancy search have been proposed to solve the problem