PHARMACEUTICAL SCHEDULING USING SIMULATED ANNEALING AND STEEPEST DESCENT METHOD

In the pharmaceutical manufacturing world, a deadline could be the difference between losing a multimillion-dollar contract or extending it. This, among many other reasons, is why good scheduling methods are vital. This problem report addresses Flexible Flowshop (FF) scheduling using Simulated Annealing (SA) in conjunction with the Steepest Descent heuristic (SD). FF is a generalized version of the flowshop problem, where each product goes through S number of stages, where each stage has M number of machines. As opposed to a normal flowshop problem, all ‘jobs’ do not have to flow in the same sequence from stage to stage. The SA metaheuristic is a global optimization method for solving hard combinatorial optimization problems. SD is a local search method that keeps track only of the current solution and moves only to neighboring permutations based on the largest decrease in the objective function value. The goal of this problem report is to use FF in conjunction with SA to minimize the makespan (length of schedule) in a pharmaceutical manufacturing environment. There are 4 total stages in the tentative production route: granulation, compression, coating, and packaging. This process will be uniform; as in, each stage will have the same number of identical machines. In this study, SA solved the illustrative small-scale example problems precisely and efficiently using a very small amount of computation time. Afterward, the SD heuristic is used to ensure that the best solution found by SA is a local optimum. SD did not improve upon the solutions found by SA

Sessenta anos de Shop Scheduling : uma revisão sistemática da literatura

Orientador : Prof. Dr. Cassius Tadeu ScarpinDissertação (mestrado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Engenharia de Produção. Defesa: Curitiba, 09/02/2017Inclui referências : f. 449-492Resumo: Desde o seminal artigo de Johnson em 1954, a Programação da Produção em Shop Scheduling tem se tornado uma área relevante dentro da Pesquisa Operacional e, atualmente, duzentos trabalhos tangentes à temática são publicados anualmente. Dentre os artigos aqui citados tem-se aqueles que se dedicam à apresentação e síntese do estado da arte desse assunto, intitulados artigos de revisão. Quando tais artigos são elaborados a partir de um conjunto objetivo de critérios, relativos à categorização dos artigos selecionados, tem-se a Revisão Sistemática da Literatura (RSL). O presente trabalho realiza uma RSL em Shop Scheduling, a partir da análise de cada ambiente fabril que o compõe. Fez-se o escrutínio de 560 artigos, à luz de um conjunto de métricas, que constitui a estrutura basilar da proposta de nova taxonomia do Shop Scheduling, complementar à notação de Graham, objetivo fulcral do presente trabalho. Além disso, utilizou-se uma representação em redes dos resultados obtidos em algumas das métricas empregadas, como a característica dos itens, algo outrora inaudito em estudos de revisão desse assunto. Ademais, outro ponto relevante desse estudo repousa na identificação de campos pouco explorados, de modo a colaborar com a pesquisa futura neste tomo. Palavras-chave: Shop Scheduling. Revisão Sistemática da Literatura. Taxonomia. Representação em Redes.Abstract: Since Johnson's seminal article in 1954, Shop Scheduling in Production Scheduling has become a relevant area within Operational Research, and currently hundreds of tangential works on the subject are published annually. Among the articles cited here are those dedicated to the presentation and synthesis of the state of the art of this subject, which are entitled review articles. When these articles are elaborated from an objective set of criteria, regarding the categorization of the selected articles, we have the Systematic Review of Literature (SLR). The present work performs a SLR in Shop Scheduling, based on the analysis of each manufacturing environment that composes it. There were 560 articles scrutinized based on a set of metrics, which is the basic structure of the proposed new Taxonomy of Shop Scheduling, complementary to Graham's notation, the main objective of this work. In addition to that a network representation of the results was obtained in some of the metrics used, such as the job characteristics, something previously unheard of in review studies of this subject. Moreover, another relevant point of this study lies in the identification of less explored fields in order to collaborate with future research in this matter. Keywords: Shop Scheduling. Systematic Literature Review. Taxonomy. Network Representation

The investigation of the effect of scheduling rules on FMS performance

The application of Flexible Manufacturing Systems (FMSs) has an effect in competitiveness, not only of individual companies but of those countries whose manufactured exports play a significant part in their economy (Hartley, 1984). However, the increasing use of FM Ss to effectively provide customers with diversified products has created a significant set of operational challenges for managers (Mahmoodi et al., 1999). In more recent years therefore, there has been a concentration of effort on FMS scheduling without which the benefits of an FMS cannot be realized. The objective of the reported research is to investigate and extend the contribution which can be made to the FMS scheduling problem through the implementation of computer-based experiments that consider real-time situations. [Continues.

Decision support systems for task scheduling: applications in manufacturing and healthcare

Esta Tesis se centra en el problema de la programación de tareas. Aunque pueden encontrarse diferentes definiciones de la programación de tareas en la literatura, aquí se define como la asignación de un número de tareas – acciones individuales que deben realizarse para completar un determinado proceso-, a un conjunto de recursos, en momentos de tiempo específicos. Pueden encontrarse ejemplos de programación de tareas en muchos contextos, como por ejemplo, el orden en el que deben fabricarse las diferentes partes de un coche, la asignación de quirófanos y cirujanos a intervenciones quirúrgicas en un hospital, o el orden en el que deben ser servidos los clientes de un restaurante. La programación de tareas supone un elemento clave en muchas compañías, en el campo de los servicios y en el de la fabricación, ya que es esencial para la coordinación del trabajo entre los diferentes actores involucrados, tales como departamentos, recursos (físicos y humanos) o entidades externas. En la mayoría de los casos, la programación de tareas conlleva trabajar con grandes cantidades de datos relacionados con el proceso y gestionar correctamente el conjunto de restricciones que controlan el proceso. Como consecuencia de esto, la programación de tareas suele hacerse con ayuda de herramientas informáticas que ofrecen algún tipo de soporte para el decisor. A este respecto, el auge de las Tecnologías de la Información (TI) en las últimas décadas ha ayudado enormemente al desarrollo de sistemas computarizados que ofrecen soporte a la toma de decisiones – Sistemas de Soporte a la Decisión (SSD) – en muchos ámbitos, incluyendo la programación de tareas. Además, ha habido un notable aumento en la capacidad computacional que ha hecho posible afrontar problemas de programación de tareas que se consideraban irresolubles hace algunos años. A pesar de estos avances, se ha detectado un gap entre teoría y práctica al llevar estas nuevas condiciones a la práctica, que puede ser demostrado por el limitado número de sistemas que se han implementado y aceptado por los usuarios satisfactoriamente. La hipótesis de trabajo de esta Tesis es que, para reducir este gap entre teoría y práctica, estos sistemas deberían considerar un conjunto de aspectos que se han estudiado en la literatura pero que no se han tenido en cuenta en el proceso de implementación, tales como el rol del decisor en el sistema, el contexto organizacional donde se toman las decisiones para la programación o la consideración de la programación como un proceso dinámico. Normalmente, cada vez que una empresa necesita implementar un SSD para la programación de tareas (SSDPT), es posible elegir entre dos opciones: adquirir una solución off-the-shelf, o diseñar y desarrollar una herramienta personalizada. Cuando se elige la primera opción, normalmente la solución no se adapta perfectamente a las actividades de la empresa, y considerando que la programación de tareas es muy dependiente del contexto, esta opción puede resultar en una situación muy documentada en la literatura en la que se consigue una implementación muy limitada en la que hay diferentes sistemas de información trabajando en paralelo para tener en cuenta las diferentes especificidades de la empresa. Por otro lado, si se opta por la segunda opción, esta suele derivar en largos tiempos de implementación con resultados pobres, ya que el equipo de desarrollo podría no tener en cuenta los errores y aciertos de otras implementaciones, tales como las funcionalidades que un sistema debería tener o los perfiles que se debería dar a los diferentes usuarios. Como resumen podríamos decir que el diseño y la implementación de SSDPT tienen un conjunto de problemas que constituyes una de las principales causas del gap existente entre la teoría de la programación de tareas y su implementación en la práctica. Para mejorar la actividad de diseño y desarrollo de SSDPT, el objetivo de esta tesis es proponer un framework común para el desarrollo de SSDPT. Para asegurar su validez y analizar su rango de aplicación, se analiza su factibilidad en dos sectores de aplicación, fabricación y salud, y se llevan a cabo dos casos de estudio en estos sectores. Para conseguir el objetivo general de la Tesis, se consideran un conjunto de objetivos específicos: 1. Proponer un framework para el diseño y desarrollo de SSDPT. • El framework tiene en cuenta todos los problemas detectados en la literatura que tienen que ver con los fallo a la hora de implementar este tipo de sistemas. Este framework se detalla mediante un conjunto de perspectivas. 2. Analizar las implementaciones existentes de SSDPT para analizar la alineación del framework propuesto con las implementaciones existentes de este tipo de sistemas en los dos campos de aplicación. • Se lleva a cabo una revisión sistemática de la literatura en SSDPT en fabricación. Las contribuciones revisadas se clasifican de acuerdo a las funcionalidades que presentan. Se analizan y discuten una serie de resultados y conclusiones de los mismos. Además se realiza una revisión de SSDPT comerciales para la programación de quirófanos. Estas contribuciones también se clasifican según sus funcionalidades y se presentan y discuten una serie de resultados y conclusiones. 3. Levar a cabo el diseño e implementación de dos SSDPT de acuerdo con el framework propuesto para demostrar su validez. • Basándonos en el framework un SSDPT para fabricación y un SSDPT para la programación de quirófanos han sido propuestos: i. El SSDPT para fabricación se implementó para una empresa de fabricación situada en Sevilla. Primero se describe el contexto en el que el sistema actúa y el problema considerado. Después se estudian los principales casos de uso del sistema y se relacionan con el framework propuesto. Más tarde, se proponen una serie de métodos de resolución eficientes para el problema analizado. Finalmente, se realiza una breve discusión sobre los principales resultados de implementación del sistema. ii. El SSDPT para programación de quirófanos se implementó en un hospital situado en Sevilla. Primero se describe el contexto en el que el sistema actúa y el problema considerado. Después se estudian los principales casos de uso del sistema y se relacionan con el framework propuesto. Más tarde, se proponen una serie de métodos de resolución eficientes para el problema analizado. Finalmente, se realiza una breve discusión sobre los principales resultados de implementación del sistema.This thesis focuses on the problem of task scheduling. Although slightly different definitions of task scheduling can be found in the literature, here it is defined as the allocation of a number of tasks - single actions that must be performed to complete a specific process-, to a set of resources, at specific moments in time. Examples of task scheduling can be found in many settings, as for example, the order in which the different parts of a car have to be manufactured in a set of machines, the allocation of operating rooms and surgeons to the surgical interventions in a hospital, or the order in which the customers of a restaurant should be served. Clearly, task scheduling is a core activity of many companies, both in manufacturing and in services, as it is essential for the coordination of the work between the different involved actors, such as departments, resources (human and physical) or external entities. In most settings, task scheduling involves treating large amounts of data related to the process and properly handling the set of constraints controlling this process. As a consequence, task scheduling is usually carried out with the help of computer tools that offer some type of support to the decision maker. In this regard, the rising of Information Technologies (ITs) in the last decades has helped enormously to develop computer systems providing support for decision making - i.e. Decision Support Systems (DSSs) - for many decisions, including task scheduling. At the same time, there has been a notable increase in computer capacity that has made possible facing task scheduling problems that were considered unsolvable some years ago. Despite these advances, an important gap between theory and practice has been found when translating these new conditions into practice, as it can be proven by the relatively short number of documented systems that have been correctly implemented and accepted by users. The working hypothesis in this Thesis is that, in order to reduce this gap between theory and practice, these tools should consider a number of aspects that have been studied in the literature but that have not been taken into account in practice during the implementation process, such as the role of the decision makers in these tools, the organisational context where scheduling decisions take place or the consideration of scheduling as a dynamic process. Typically, each time a company requires to implement of a DSS for task scheduling, in the following DSSTS, it faces two different options: either acquiring an off-the-shelf solution, or designing and developing an in-house tool. If the former option is chosen, the acquired solution may not fit perfectly into the activities of the company, and, since task scheduling is company-specific, this approach may result in a situation widely documented in the literature where there exist limited implementations that needs information systems working in parallel to deal with the specificities of the company. On the contrary, the second option usually derives in large implementation times with poor results, as the development team may not take into account errors or successes from former implementations, such as the functionalities that the system should include or the profiles required for the decision makers among others. As a summary, the design and implementation of DSSTS suffer a number of problems which constitute a root cause for the existing gap between the scheduling theory and its implementation into practice. In order to improve the activity of designing and developing DSSTS, the aim of this thesis is to propose a common framework for the development of DSSTS. In order to ensure the validity and range of application of this framework, its feasibility is analysed within two specific fields of applications, namely manufacturing and healthcare, and two implementation case studies are conducted within these fields. In order to fullfil this general objective, a number of specific objectives can be detailed: 1. To propose a framework for the design and development of DSSTS. • This framework address all the issues found in literature regarding the common failures when implementing this type of systems. A number of perspectives of the framework are given in order to properly detail it. 2. To analyse existing implementations of DSSTS in order to check the alignment of the framework proposed with the task scheduling systems implemented in the two sectors chosen for the evaluation of the framework. • A systematic literature review on manufacturing DSSTS is carried out. The reviewed contributions are classified according to their functionalities. A number of findings and conclusions about these findings are discussed. Additionally, a review on commercial operating room DSSTS is done. These contributions are also classified according to their functionality and a number of findings and conclusions about these findings are discussed. 3. To conduct the design and implementation of two DSSTS according to the proposed framework in order to demonstrate its applicability. • Based on the proposed framework, a manufacturing DSSTS and an operating room DSSTS are implemented: i. The manufacturing DSSTS is applied to a real manufacturing company in Sevilla. First, we describe the context where the DSSTS is deployed and the problem addressed, i.e. the hybrid flowshop scheduling problem with missing operations. Then, the main use cases of the DSSTS are discussed and related to the framework. Next, a set of efficient solution procedures for the problem under study are proposed. And finally, a brief discussion on the main results of the implementation of the DSSTS is carried out. ii. The operating room DSSTS is applied to a real hospital in Sevilla. First, we describe the context where the DSSTS is deployed and the problem addressed, i.e. the the operating room scheduling problem. Then, the main use cases of the DSSTS are discussed and related to the framework. Next, a set of efficient solution procedures for the problem under study are proposed. And finally, a brief discussion on the main results of the implementation of the DSSTS is carried out

Scheduling with tool changes to minimize total completion time

Ankara : Department of Industrial Engineering and Institute of Engineerin and Sciences, Bilkent Univ., 1998.Thesis (Master's) -- Bilkent University, 1998.Includes bibliographical references leaves 87-90.In the literature, scheduling models do not consider the unavailability of tools. The tool management literature separately considers tool loading problem when tool changes are due to part mix. However in manufacturing settings tools are changed more often due to tool wear. In this research, the problem of scheduling a set of jobs to minimize total completion time on a single CNC machine is considered where the cutting tool is subject to wear. We show that this problem is NP-hard in the strong sense. We discuss the behavior of SPT heuristic and show that its worst case performance ratio is bounded above by a constant. A pseudo-polynomial dynamic programming formulation is provided to solve the problem optimally. Furthermore, heuristic algorithms are developed including dispatching heuristics and local search algorithms. It is observed that the performance of SPT rule gets worse as the tool change time increases and tool life decreases. The best improvement over the SPT rule’s performance is achieved by the proposed genetic algorithm with problem space search.Güneş, Evrim DidemM.S

Optimization Models and Approximate Algorithms for the Aerial Refueling Scheduling and Rescheduling Problems

The Aerial Refueling Scheduling Problem (ARSP) can be defined as determining the refueling completion times for fighter aircrafts (jobs) on multiple tankers (machines) to minimize the total weighted tardiness. ARSP can be modeled as a parallel machine scheduling with release times and due date-to-deadline window. ARSP assumes that the jobs have different release times, due dates, and due date-to-deadline windows between the refueling due date and a deadline to return without refueling. The Aerial Refueling Rescheduling Problem (ARRP), on the other hand, can be defined as updating the existing AR schedule after being disrupted by job related events including the arrival of new aircrafts, departure of an existing aircrafts, and changes in aircraft priorities. ARRP is formulated as a multiobjective optimization problem by minimizing the total weighted tardiness (schedule quality) and schedule instability. Both ARSP and ARRP are formulated as mixed integer programming models. The objective function in ARSP is a piecewise tardiness cost that takes into account due date-to-deadline windows and job priorities. Since ARSP is NP-hard, four approximate algorithms are proposed to obtain solutions in reasonable computational times, namely (1) apparent piecewise tardiness cost with release time rule (APTCR), (2) simulated annealing starting from random solution (SArandom ), (3) SA improving the initial solution constructed by APTCR (SAAPTCR), and (4) Metaheuristic for Randomized Priority Search (MetaRaPS). Additionally, five regeneration and partial repair algorithms (MetaRE, BestINSERT, SEPRE, LSHIFT, and SHUFFLE) were developed for ARRP to update instantly the current schedule at the disruption time. The proposed heuristic algorithms are tested in terms of solution quality and CPU time through computational experiments with randomly generated data to represent AR operations and disruptions. Effectiveness of the scheduling and rescheduling algorithms are compared to optimal solutions for problems with up to 12 jobs and to each other for larger problems with up to 60 jobs. The results show that, APTCR is more likely to outperform SArandom especially when the problem size increases, although it has significantly worse performance than SA in terms of deviation from optimal solution for small size problems. Moreover CPU time performance of APTCR is significantly better than SA in both cases. MetaRaPS is more likely to outperform SAAPTCR in terms of average error from optimal solutions for both small and large size problems. Results for small size problems show that MetaRaPS algorithm is more robust compared to SAAPTCR. However, CPU time performance of SA is significantly better than MetaRaPS in both cases. ARRP experiments were conducted with various values of objective weighting factor for extended analysis. In the job arrival case, MetaRE and BestINSERT have significantly performed better than SEPRE in terms of average relative error for small size problems. In the case of job priority disruption, there is no significant difference between MetaRE, BestINSERT, and SHUFFLE algorithms. MetaRE has significantly performed better than LSHIFT to repair job departure disruptions and significantly superior to the BestINSERT algorithm in terms of both relative error and computational time for large size problems

Four decades of research on the open-shop scheduling problem to minimize the makespan

One of the basic scheduling problems, the open-shop scheduling problem has a broad range of applications across different sectors. The problem concerns scheduling a set of jobs, each of which has a set of operations, on a set of different machines. Each machine can process at most one operation at a time and the job processing order on the machines is immaterial, i.e., it has no implication for the scheduling outcome. The aim is to determine a schedule, i.e., the completion times of the operations processed on the machines, such that a performance criterion is optimized. While research on the problem dates back to the 1970s, there have been reviving interests in the computational complexity of variants of the problem and solution methodologies in the past few years. Aiming to provide a complete road map for future research on the open-shop scheduling problem, we present an up-to-date and comprehensive review of studies on the problem that focuses on minimizing the makespan, and discuss potential research opportunities

An improved memetic algorithm to solve the energy-efficient distributed flexible job shop scheduling problem with transportation and start-stop constraints

In the current global cooperative production environment, modern industries are confronted with intricate production plans, demanding the adoption of contemporary production scheduling strategies. Within this context, distributed manufacturing has emerged as a prominent trend. Manufacturing enterprises, especially those engaged in activities like automotive mold production and welding, are facing a significant challenge in managing a significant amount of small-scale tasks characterized by short processing times. In this situation, it becomes imperative to consider the transportation time of jobs between machines. This paper simultaneously considers the transportation time of jobs between machines and the start-stop operation of the machines, which is the first time to our knowledge. An improved memetic algorithm (IMA) is proposed to solve the multi-objective distributed flexible job shop scheduling problem (MODFJSP) with the goal of minimizing maximum completion time and energy consumption. Then, a new multi-start simulated annealing algorithm is proposed and integrated into the IMA to improve the exploration ability and diversity of the algorithm. Furthermore, a new multiple-initialization rule is designed to enhance the quality of the initial population. Additionally, four improved variable neighborhood search strategies and two energy-saving strategies are designed to enhance the search ability and reduce energy consumption. To verify the effectiveness of the IMA, we conducted extensive testing and comprehensive evaluation on 20 instances. The results indicate that, when faced with the MODFJSP, the IMA can achieve better solutions in almost all instances, which is of great significance for the improvement of production scheduling in intelligent manufacturing

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

Group-scheduling problems in electronics manufacturing

This dissertation addresses the "multi-machine carryover sequence dependent group-scheduling problem with anticipatory setups," which arises in the printed circuit board (PCB) manufacturing. Typically, in PCB manufacturing different board types requiring similar components are grouped together to reduce setup times and increase throughput. The challenge is to determine the sequence of board groups as well as the sequence of individual board types within each group. The two separate objectives considered are minimizing the makespan and minimizing the mean flow time. In order to quickly solve the problem with each of the two objectives, highly effective metasearch heuristic algorithms based on the concept known as tabu search are developed. Advanced features of tabu search, such as the long-term memory function in order to intensify/diversify the search and variable tabu-list sizes, are utilized in the proposed heuristics. In the absence of knowing the actual optimal solutions, another important challenge is to assess the quality of the solutions identified by the proposed metaheuristics. For that purpose, methods that identify strong lower bounds both on the optimal makespan and the optimal mean flow time are proposed. The quality of a heuristic solution is then quantified as its percentage deviation from the lower bound. Based on the minimum possible setup times, this dissertation develops a lower bounding procedure, called procedure Minsetup, that is capable of identifying tight lower bounds. Even tighter lower bounds are identified using a mathematical programming decomposition approach. Novel mathematical programming formulations are developed and a branch-and-price (B&P) algorithm is proposed and implemented. A Dantzig-Wolfe reformulation of the problem that enables applying a column generation algorithm to solve the linear programming relaxation of the master problem is presented. Single-machine subproblems are designed to identify new columns if and when necessary. To enhance the efficiency of the algorithm, approximation algorithms are developed to solve the subproblems. Effective branching rules partition the solution space of the problem at a node where the solution is fractional. In order to alleviate the slow convergence of the column generation process at each node, a stabilizing technique is developed. Finally, several implementation issues such as constructing a feasible initial master problem, column management, and search strategy, are addressed. The results of a carefully designed computational experiment for both low-mix high-volume and high-mix low-volume production environments confirm the high performance of tabu search algorithms in identifying extremely good quality solutions with respect to the proposed lower bounds