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

Aproximações heurísticas para um problema de escalonamento do tipo flexible job-shop

Mestrado em Engenharia e Gestão IndustrialEste trabalho aborda um novo tipo de problema de escalonamento que pode ser encontrado em várias aplicações do mundo-real, principalmente na indústria transformadora. Em relação à configuração do shop floor, o problema pode ser classificado como flexible job-shop, onde os trabalhos podem ter diferentes rotas ao longo dos recursos e as suas operações têm um conjunto de recursos onde podem ser realizadas. Outras características de processamento abordadas são: datas possíveis de início, restrições de precedência (entre operações de um mesmo trabalho ou entre diferentes trabalhos), capacidade dos recursos (incluindo paragens, alterações na capacidade e capacidade infinita) e tempos de setup (que podem ser dependentes ou independentes da sequência). O objetivo é minimizar o número total de trabalhos atrasados. Para resolver o novo problema de escalonamento proposto um modelo de programação linear inteira mista é apresentado e novas abordagens heurísticas são propostas. Duas heurísticas construtivas, cinco heurísticas de melhoramento e duas metaheurísticas são propostas. As heurísticas construtivas são baseadas em regras de ordenação simples, onde as principais diferenças entre elas dizem respeito às regras de ordenação utilizadas e à forma de atribuir os recursos às operações. Os métodos são designados de job-by-job (JBJ), operation-by-operation (OBO) e resource-by-resource (RBR). Dentro das heurísticas de melhoramento, a reassign e a external exchange visam alterar a atribuição dos recursos, a internal exchange e a swap pretendem alterar a sequência de operações e a reinsert-reassign é focada em mudar, simultaneamente, ambas as partes. Algumas das heurísticas propostas são usadas em metaheurísticas, nomeadamente a greedy randomized adaptive search procedure (GRASP) e a iterated local search (ILS). Para avaliar estas abordagens, é proposto um novo conjunto de instâncias adaptadas de problemas de escalonamento gerais do tipo flexible job-shop. De todos os métodos, o que apresenta os melhores resultados é o ILS-OBO obtendo melhores valores médios de gaps em tempos médios inferiores a 3 minutos.This work addresses a new type of scheduling problem which can be found in several real-world applications, mostly in manufacturing. Regarding shop floor configuration, the problem can be classified as flexible job-shop, where jobs can have different routes passing through resources and their operations have a set of eligible resources in which they can be performed. The processing characteristics addressed are release dates, precedence constraints (either between operations of the same job or between different jobs), resources capacity (including downtimes, changes in capacity, and infinite capacity), and setup times, which can be sequence-dependent or sequence-independent. The objective is to minimise the total number of tardy jobs. To tackle the newly proposed flexible job-shop scheduling problem (FJSP), a mixed integer linear programming model (MILP) is presented and new heuristic approaches are put forward. Three constructive heuristics, five improvement heuristics, and two metaheuristics are proposed. The constructive heuristics are based on simple dispatching rules, where the main differences among them concern the used dispatching rules and the way resources are assigned. The methods are named job-by-job (JBJ), operation-by-operation (OBO) and resource-by-resource (RBR). Within improvement heuristics, reassign and external exchange aim to change the resources assignment, internal exchange and swap intend changing the operations sequence, and reinsert-reassign is focused in simultaneously changing both parts. Some of the proposed heuristics are used within metaheuristic frameworks, namely greedy randomized adaptive search procedure (GRASP) and iterative local search (ILS). In order to evaluate these approaches, a new set of benchmark instances adapted from the general FJSP is proposed. Out of all methods, the one which shows the best average results is ILS-OBO obtaining the best average gap values in average times lower than 3 minutes

Makespan Minimization in Re-entrant Permutation Flow Shops

Re-entrant permutation flow shop problems occur in practical applications such as wafer manufacturing, paint shops, mold and die processes and textile industry. A re-entrant material flow means that the production jobs need to visit at least one working station multiple times. A comprehensive review gives an overview of the literature on re-entrant scheduling. The influence of missing operations received just little attention so far and splitting the jobs into sublots was not examined in re-entrant permutation flow shops before. The computational complexity of makespan minimization in re-entrant permutation flow shop problems requires heuristic solution approaches for large problem sizes. The problem provides promising structural properties for the application of a variable neighborhood search because of the repeated processing of jobs on several machines. Furthermore the different characteristics of lot streaming and their impact on the makespan of a schedule are examined in this thesis and the heuristic solution methods are adjusted to manage the problem’s extension

Serial-batch scheduling – the special case of laser-cutting machines

The dissertation deals with a problem in the field of short-term production planning, namely the scheduling of laser-cutting machines. The object of decision is the grouping of production orders (batching) and the sequencing of these order groups on one or more machines (scheduling). This problem is also known in the literature as "batch scheduling problem" and belongs to the class of combinatorial optimization problems due to the interdependencies between the batching and the scheduling decisions. The concepts and methods used are mainly from production planning, operations research and machine learning

Sequencing in Mixed Model Non-Permutation Flowshop Production Lines using Constrained Buffers

En una línea de producción clásica, solamente se producían productos con las mismas opciones. Para la fabricación de variaciones del mismo producto básico se utilizaba una línea diferente o eran necesarias modificaciones importantes de la maquinaria. En los últimos años se ha visto acrecentada la necesidad de considerar métodos que permitan más flexibilidad ofreciendo una mayor variedad de productos al cliente. En general estos métodos consisten en producir diferentes tipos de productos en una misma línea de producción. Además, con la filosofía de Just-In-Time, los stocks y sus costes derivados, especialmente el stock de productos acabados, se reducen considerablemente y consecuentemente una producción con lotes ya no es favorable. Con este panorama la producción de distintos productos o modelos en la misma línea de forma simultánea, sin lotes, adquiere un gran auge y con ello la complejidad de gestión de la línea aumenta. La toma de decisiones en las fases de secuenciación y programación se convierte en esencial.Existen varios diseños de líneas que pueden permitir la resecuenciación, como son:utilizar grandes almacenes (Automatic-Storage-and-Retrieval-System), desacoplar una parte del proceso del resto de la línea; disponer de almacenes con plazas limitadas fuera de la línea; existencia de líneas híbridas o flexibles; posibilitar la división y unión de líneas;o cambiar los atributos de las piezas en vez de cambiar la posición en la secuencia. La resecuenciación de piezas dentro de la línea llega ser más efectiva cuando se presenta un tiempo o coste adicional, conocido como setup-time y setup-cost, necesario en muchos casos, cuando en una estación, la siguiente pieza es de otro modelo.Esta tesis considera el caso de una línea de flujo con la posibilidad de resecuenciar piezas entre estaciones consecutivas. Los almacenes están ubicados fuera de la línea y en un primer paso accesible desde una sola estación (caso del almacén intermedio). A continuación se utilizará un solo almacén, centralizado, accesible desde varias estaciones. En ambos casos se considera que una pieza, debido a su tamaño, quizás no pueda ocupar ciertas plazas del almacén ya sea intermedio o centralizado. Como resultado del estudio y análisis del Estado del Arte, que permitió delimitar el caso a estudiar, se propone una Novedosa Clasificación de líneas de flujo no permutación. Esta clasificación era indispensable, debido a que en la literatura actual no se ha clasificado con profundidad este tipo de producción, hasta hoy las clasificaciones existentes no consideran las múltiples opciones que se presentan al incluir la posibilidad de resecuenciar piezas en la línea. La presente tesis presenta distintas formulaciones: un método exacto, utilizando un modelo de programación por restricciones (CLP), varios métodos híbridos, basados en CLP, y un método heurístico, utilizando un Algoritmo Genético (GA).Durante el curso de este trabajo, los estudios que se han realizado muestran la efectividad de resecuenciar. Los resultados de los experimentos simulados muestran los beneficios que sumergen con un almacén centralizado, comparado con los almacenes intermedios.El problema considerado es relevante para una variedad de aplicaciones de líneas de flujo como es el caso de la industria química, donde los pedidos de los clientes tienen diferentes volúmenes y en la misma línea existen tanques de diferentes volúmenes para resecuenciar. También, en líneas en las cuales se utilizan lotes divididos (split-lot) con el fin de investigar variaciones en los procesos, así como en la industria de semiconductores, o en la producción de casas prefabricadas, donde fabrican paredesgrandes y pequeñas que pasan por estaciones consecutivas y en las que se instalan circuitos eléctricos, tuberías, puertas, ventanas y aislamientos.In the classical production line, only products with the same options were processed at once. Products of different models, providing distinct options, were either processed on a different line or major equipment modifications were necessary. For today's production lines approaches, considering more flexibility, are required which result more and more in the necessity of manufacturing a variety of different models on the same line, motivated by offering a larger variety of products to the client. Furthermore, with the Just-In-Time philosophy, the stock and with that the expenses derived from it, especially for finished products, are considerably reduced and lead to the case in which a production with batches is no longer favourable.Taking into account this panorama, the simultaneous production of distinct products ormodels in the same line, without batches, lead to an increased importance and at the same time the logistic complexity enlarges. The decision-making in sequencing and scheduling become essential.Various designs of production lines exist which permit resequencing of jobs within the production line: using large buffers (Automatic-Storage-and-Retrieval-System) which decouple one part of the line from the rest of the line; buffers which are located offline; hybrid or flexible lines; and more seldom, the interchange of job attributes instead of physically changing the position of a job within the sequence. Resequencing of jobs within the line is even more relevant with the existence of an additional cost or time, occurring when at a station the succeeding job is of another model, known as setup cost and setup time.The present thesis considers a flowshop with the possibility to resequence jobs between consecutive stations. The buffers are located offline either accessible from a single station (intermediate case) or from various stations (centralized case). In both cases, it is considered that a job may not be able to be stored in a buffer place, due to its extended physical size.Following the extensive State-of-the-Art, which led to the problem under study, a Novel Classification of Non-permutation Flowshops is proposed. This classification was indispensable, due to the lack of an adequate classification for flowshop production lines that would consider the diversity of arrangements which permit resequencing of jobs within the production line. Furthermore, distinct formulations are presented: an exact approach, utilizing Constrained Logic Programming (CLP), various hybrid approaches, based on CLP, and a heuristic approach, utilizing a Genetic Algorithm (GA).During the course of this work, the realized studies of performance demonstrate the effectiveness of resequencing. The results of the simulation experiments reveal the benefits that come with a centralized buffer location, compared to the intermediate buffer location.The considered problem is relevant to various flowshop applications such as chemical productions dealing with client orders of different volumes and different sized resequencing tanks. Also in productions where split-lots are used for engineering purpose, such as the semiconductor industry. Even in the production of prefabricated houses with, e.g., large and small walls passing through consecutive stations where electrical circuits, sewerage, doors, windows and isolation are applied

An integer programming approach for Balancing and Scheduling in Extended Manufacturing Environment

In the fiercely competitive era induced by expansion of open business archetypes, the managerial aspects of Extended Manufacturing Environments (EMEs) are experiencing growing concerns. There is no scope of leaving a possible operational improvement unexplored. For enhanced operational efficiency and capacity utilization the balancing and scheduling problems of EMEs are, therefore, rightfully considered and an integer programme is proposed in this paper. The model is designed in a spread sheet and solved through What'sBest optimizer. The model capabilities is assessed through a test problem. The results have demonstrated that the model is capable of defining optimized production schedules for EMEs.This study has been conducted under FRGS project (FRGS14- 102-0343) funded by Ministry of Higher Education (MOHE), Malaysia. The authors are grateful to MOHE and Research Management Centre (RMC), International Islamic University Malaysia (IIUM) for their support.info:eu-repo/semantics/publishedVersio

A Production Planning Model for Make-to-Order Foundry Flow Shop with Capacity Constraint

The mode of production in the modern manufacturing enterprise mainly prefers to MTO (Make-to-Order); how to reasonably arrange the production plan has become a very common and urgent problem for enterprises’ managers to improve inner production reformation in the competitive market environment. In this paper, a mathematical model of production planning is proposed to maximize the profit with capacity constraint. Four kinds of cost factors (material cost, process cost, delay cost, and facility occupy cost) are considered in the proposed model. Different factors not only result in different profit but also result in different satisfaction degrees of customers. Particularly, the delay cost and facility occupy cost cannot reach the minimum at the same time; the two objectives are interactional. This paper presents a mathematical model based on the actual production process of a foundry flow shop. An improved genetic algorithm (IGA) is proposed to solve the biobjective problem of the model. Also, the gene encoding and decoding, the definition of fitness function, and genetic operators have been illustrated. In addition, the proposed algorithm is used to solve the production planning problem of a foundry flow shop in a casting enterprise. And comparisons with other recently published algorithms show the efficiency and effectiveness of the proposed algorithm