Multicriteria hybrid flow shop scheduling problem: literature review, analysis, and future research

This research focuses on the Hybrid Flow Shop production scheduling problem, which is one of the most difficult problems to solve. The literature points to several studies that focus the Hybrid Flow Shop scheduling problem with monocriteria functions. Despite of the fact that, many real world problems involve several objective functions, they can often compete and conflict, leading researchers to concentrate direct their efforts on the development of methods that take consider this variant into consideration. The goal of the study is to review and analyze the methods in order to solve the Hybrid Flow Shop production scheduling problem with multicriteria functions in the literature. The analyses were performed using several papers that have been published over the years, also the parallel machines types, the approach used to develop solution methods, the type of method develop, the objective function, the performance criterion adopted, and the additional constraints considered. The results of the reviewing and analysis of 46 papers showed opportunities for future researchon this topic, including the following: (i) use uniform and dedicated parallel machines, (ii) use exact and metaheuristics approaches, (iv) develop lower and uppers bounds, relations of dominance and different search strategiesto improve the computational time of the exact methods,  (v) develop  other types of metaheuristic, (vi) work with anticipatory setups, and (vii) add constraints faced by the production systems itself

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

Variable Neighborhood Search for Parallel Machines Scheduling Problem with Step Deteriorating Jobs

In many real scheduling environments, a job processed later needs longer time than the same job when it starts earlier. This phenomenon is known as scheduling with deteriorating jobs to many industrial applications. In this paper, we study a scheduling problem of minimizing the total completion time on identical parallel machines where the processing time of a job is a step function of its starting time and a deteriorating date that is individual to all jobs. Firstly, a mixed integer programming model is presented for the problem. And then, a modified weight-combination search algorithm and a variable neighborhood search are employed to yield optimal or near-optimal schedule. To evaluate the performance of the proposed algorithms, computational experiments are performed on randomly generated test instances. Finally, computational results show that the proposed approaches obtain near-optimal solutions in a reasonable computational time even for large-sized problems

A research survey: review of flexible job shop scheduling techniques

In the last 25 years, extensive research has been carried out addressing the flexible job shop scheduling (JSS) problem. A variety of techniques ranging from exact methods to hybrid techniques have been used in this research. The paper aims at presenting the development of flexible JSS and a consolidated survey of various techniques that have been employed since 1990 for problem resolution. The paper comprises evaluation of publications and research methods used in various research papers. Finally, conclusions are drawn based on performed survey results. A total of 404 distinct publications were found addressing the FJSSP. Some of the research papers presented more than one technique/algorithm to solve the problem that is categorized into 410 different applications. Selected time period of these research papers is between 1990 and February 2014. Articles were searched mainly on major databases such as SpringerLink, Science Direct, IEEE Xplore, Scopus, EBSCO, etc. and other web sources. All databases were searched for “flexible job shop” and “scheduling” in the title an

Heuristic Algorithm to Minimize Total Weighted Tardiness on the Unrelated Parallel Machine with Sequence Dependent Setup and Future Ready Time

This study presents a heuristic algorithm to minimize total weighted tardiness on unrelated parallel machines with sequence-dependent setup time and future ready time. We propose a new rule based on Apparent Tardiness Cost (ATC). The performance of the rule is evaluated on unrelated parallel machines. In order to solve a problem, we use a look-ahead method and a job-swap method. When a machine becomes idle, the heuristic compares the jobs on the machine and selects the one with the smallest total tardiness value to carry out a process. The propose heuristic is divided into three stages: The first stage employs the newly introduced dispatching rule, ATC with continuous setup and ready time for unrelated parallel machines (ATCSR_UP), along with a look-ahead heuristic to select the initial job for each machine. The second stage, consisting of several iterations, schedules the rest of the job on the machine. Each iteration starts by finding the job with the smallest tardiness. The ATCSR_Rm rule proposed by Lin and Hsieh (2013) concerns the unrelated-parallel-machine scheduling which this study examines, so we compare our ATC-based rule with their proposed rule. Although they study a separable setup time in their research, no other paper than Lin and Hsieh (2003) focus on unrelated parallel machine with future ready times. In their WSPT term, they consider the processing time for each job; our own rule considers processing time, setup time, job ready time, and machine time. We consider the setup time, job ready time, and machine time because — according to the continuous sequence-dependent setup rule — setup time should be included in processing time (Yue and Jang 2013). In addition, job ready time and machine time should also be included in the processing time. Adding setup time 〖(s〗_(i,j)), job ready time (r_j), and machine time (t_m) to the formula thus makes the formula more accurate. Lin and Hsieh (2013) use max(r_j,t_i+s_(i,j) ) for the slack term, and they compare the ready time with the sum of the machine available time 〖(t〗_i) and the setup time 〖(s〗_(i,j)). However, in our formula, we consider ready time, machine time, and current time. Current time (t) is used when a job might come at a future time when the machine in question is idle or has finished the job. The last term of the propose heuristic is the ready term, which uses both ready time (r_j) and machine time (t_m), because it needs to specify whether ready time (r_j) or machine time (t_m) goes first. If a job is ready to be processed but the machine is not ready, the job has to wait. We use ready time (r_j) and machine time (t_m) because this makes the formula more suitable for practical, real-world us

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

A SearchCol Algorithm for the unrelated parallel machine scheduling problem with job splitting

Dissertação de mestrado em Engenharia IndustrialIn this dissertation, the unrelated parallel machine scheduling problem with job splitting and sequence independent setup times is addressed, implementing a method to solve it in a recently proposed framework, SearchCol, short for ‘Metaheuristic search by Column Generation’. The study of scheduling problems is of high relevance due to its real-world application in multiple fields, as documented in its vast literature, and also due to its high complexity derived from the diverse environments, variables, restrictions and the combinations of these in different systems. The problem consists in finding a scheduling plan for a set of independent jobs on a set of unrelated parallel machines, considering jobs and machines release dates, sequence independent setup times and the job splitting property, with due date related objectives. The introduction of setup times and job splitting properties in unrelated environments has not been extensively studied, even though its use can play an important role in scheduling. A mixed integer programming model is developed featuring the aforementioned properties, which is then decomposed by machine using the Dantzig-Wolfe decomposition. To solve the decomposed model a hybrid approach entitled SearchCol is applied, which results from the interaction between column generation and metaheuristics. Problem specific heuristics to use in the column generation component of the SearchCol are also developed and diverse alternatives within the global algorithm are tested. A problem specific algorithm for one of the main SearchCol components is also suggested. To evaluate the effectiveness of the model and the proposed algorithms, computational tests are performed and their solutions analysed for a set of test instances.O trabalho que se apresenta nesta dissertação, aborda o problema de escalonamento em máquinas paralelas não relacionadas com dimensionamento de lotes e tempos de preparação independentes da sequência, recorrendo a uma ferramenta recentemente proposta, designada por SearchCol, abreviatura de ‘Metaheuristic Search by Column Generation’. O estudo de problemas de escalonamento revela-se de grande importância devido à sua aplicação em diferentes áreas, documentado na sua vasta literatura, e também devido à sua elevada complexidade decorrente das diversas configurações e tipos de máquinas, variáveis e restrições, bem como as combinações destas nos diversos sistemas. O problema consiste na determinação de um plano de produção para um conjunto de tarefas independentes em máquinas paralelas não relacionadas, considerando tempos de disponibilidade de tarefas e máquinas, tempos de preparação independentes da sequência e o dimensionamento de lotes. O estudo deste problema com incorporação de tempos de preparação e da propriedade de dimensionamento de lotes em máquinas paralelas não relacionadas não é comum na literatura, apesar de se revelar de extrema importância em problemas de escalonamento. Um modelo de programação inteira mista é desenvolvido para o problema e é também efectuada uma decomposição por máquina através da decomposição de Dantzig-Wolfe. Para resolver o problema, estuda-se uma abordagem híbrida que consiste na interação entre a técnica de geração de colunas e metaheurísticas, de seu nome SearchCol. São desenvolvidas heurísticas específicas para o problema, as quais são usadas na componente de geração de colunas do SearchCol, sendo testadas também diversas alternativas e ferramentas no contexto do algoritmo global. Além disso, um algoritmo específico para o problema é também sugerido, para incluir num dos principais componentes do SearchCol. Para avaliar o desempenho e qualidade dos modelos e algoritmos propostos, são realizados testes computacionais e analisadas as suas soluções para um conjunto de instâncias de teste.Fundação para a Ciência e a Tecnologia (FCT) - Project ref. PTDC/EIA-EIA/100645/2008.This work was partially funded by the FEDER through the Programme COMPETE