Experimental evaluation of algorithms forsolving problems with combinatorial explosion

Solving problems with combinatorial explosionplays an important role in decision-making, sincefeasible or optimal decisions often depend on anon-trivial combination of various factors. Gener-ally, an effective strategy for solving such problemsis merging different viewpoints adopted in differ-ent communities that try to solve similar prob-lems; such that algorithms developed in one re-search area are applicable to other problems, orcan be hybridised with techniques in other ar-eas. This is one of the aims of the RCRA (Ra-gionamento Automatico e Rappresentazione dellaConoscenza) group,1the interest group of the Ital-ian Association for Artificial Intelligence (AI*IA)on knowledge representation and automated rea-soning, which organises its annual meetings since1994

a hybrid metaheuristic approach for minimizing the total flow time in a flow shop sequence dependent group scheduling problem

Production processes in Cellular Manufacturing Systems (CMS) often involve groups of parts sharing the same technological requirements in terms of tooling and setup. The issue of scheduling such parts through a flow-shop production layout is known as the Flow-Shop Group Scheduling (FSGS) problem or, whether setup times are sequence-dependent, the Flow-Shop Sequence-Dependent Group Scheduling (FSDGS) problem. This paper addresses the FSDGS issue, proposing a hybrid metaheuristic procedure integrating features from Genetic Algorithms (GAs) and Biased Random Sampling (BRS) search techniques with the aim of minimizing the total flow time, i.e., the sum of completion times of all jobs. A well-known benchmark of test cases, entailing problems with two, three, and six machines, is employed for both tuning the relevant parameters of the developed procedure and assessing its performances against two metaheuristic algorithms recently presented by literature. The obtained results and a properly arranged ANOVA analysis highlight the superiority of the proposed approach in tackling the scheduling problem under investigation

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

Development of a Multi-Objective Scheduling System for Complex Job Shops in a Manufacturing Environment

In many sectors of commercial operation, the scheduling of workflows and the allocation of resources at an optimum time is critical; for effective and efficient operation. The high degree of complexity of a “Job Shop” manufacturing environment, with sequencing of many parallel orders, and allocation of resources within multi-objective operational criteria, has been subject to several research studies. In this thesis, a scheduling system for optimizing multi-objective job shop scheduling problems was developed in order to satisfy different production system requirements. The developed system incorporated three different factors; setup times, alternative machines and release dates, into one model. These three factors were considered after a survey study of multiobjective job shop scheduling problems. In order to solve the multi-objective job shop scheduling problems, a combination of genetic algorithm and a modified version of a very recent and computationally efficient approach to non-dominated sorting solutions, called “efficient non-dominated sort using the backward pass sequential strategy”, was applied. In the proposed genetic algorithm, an operation based representation was designed in the matrix form, which can preserve features of the parent after the crossover operator without repairing the solution. The proposed efficient non-dominated sort using the backward pass sequential strategy was employed to determine the front, to which each solution belongs. The proposed system was tested and validated with 20 benchmark problems after they have been modified. The experimental results show that the proposed system was effective and efficient to solve multi-objective job shop scheduling problems in terms of solution quality

The permutation flowshop scheduling problem: analysis, solution procedures and problem extensions

During the past twenty five years, following the massive use of internet and the EU single Market, European manufacturing companies struggle in a more competitive market, where firms from different countries must fight for common customers. As a consequence, prices of the products have decreased and the efficiency in the production processes of the companies have become more and more important. Nowadays, this fact is also increasing due to the competition from companies in developing countries whose labour cost is substantially lower. Therefore, production management is a key element for companies to survive. Production management involves decision making over several issues such as master scheduling, material requirements planning, capacity planning, manufacturing scheduling, ... Among these decisions, manufacturing scheduling plays an essential role on resource productivity and customer service. Its role is also increasing in many service industries as transportation, computer and communications industries, which are moving towards manufacture-to-order and virtual environments. Manufacturing scheduling deals with the determination of the jobs which are processed for each resource in each instant of time, i.e. establishes the schedules of the resources along the horizon under consideration. In order to determine the best schedule for the shop floor, both the specific constraints and the goal of the shop have to be considered. In these environments, the difficulty of the scheduling problem increases and becomes NP-hard even for the most simple scheduling problems, being extremely complex for real manufacturing scenarios. Additionally, scheduling decisions should be made in short time intervals requiring a rapid response time, due to several aspects such as the lifetime of a schedule, the delay in the suppliers, arrivals of new jobs to be processed, rescheduling due to failures while processing a job, .... All these issues strongly stress the need to find fast and efficient solution procedures (i.e. heuristics and metaheuristics) for solving manufacturing scheduling problems. In practice, several processing layouts have been adopted by companies to manufacture their products. Among them, the Permutation Flowshop Scheduling Problem (PFSP in the following), which is the problem addressed in this Thesis, stands out as the most relevant, being one of the most studied problems in Operations Research. There are several reasons for this fact: On the one hand, the flow shop layout is the common configuration in many real manufacturing scenarios, as it presents several advantages over more general job shop configuration, and, in addition, many job shops are indeed a flow shop for most of the jobs. On the other hand, many models and solution procedures for different constraints and layouts have their origins in the flowshop scheduling problem, which increases the importance to find efficient algorithms for this scheduling problem. Despite the huge number of research conducted on the PFSP, we believe that there is room for improving the current state of the art in the topic by: 1. deepening the understanding of the problem with respect to their input parameters, 2. devising new approximate solution procedures for the common employed objectives, and 3. addressing problem extensions to capture more realistic situations. To carry out this goal, the following general research objectives are identified: 1. To review the PFSP literature for the most common objectives, i.e. makespan, total completion time and due-date-based objectives (total tardiness, and total earliness and tardiness). 2. To analyse the influence of the processing times and due dates of the jobs on the PFSP. 3. To provide schedulers with faster and more efficient heuristics and metaheuristics to solve the PFSP for makespan, total completion time, total tardiness, and total earliness and tardiness minimisation. 4. To demonstrate the efficiency and good performance of the solution procedures developed in Goal 3. 5. To extend the proposals in Goal 3 to some constrained PFSP based on real manufacturing environments. To achieve these objectives, the Thesis have been structured in five parts as follows: - Part I is divided into two chapters. In Chapter 1.1, we introduce this Thesis and discuss its main contributions. In Chapter 2, the problem under consideration is stated. The measures to compare approximated algorithms are discussed in Chapter 3. There, the benchmarks used to evaluated the algorithms are introduced and an alternative indicator is proposed to overcome some problems detected using the traditional ones. - In Part II, we analyse the problem in detail along three chapters. Dealing with Objective 1, the main contributions in the literature are review for the most-common objective functions in Chapter 4. Additionally, in Chapter 5, we extensively study the behaviour of the problem depending on the configuration of the shops, i.e. processing times and due dates of the jobs (see Goal 2). - In Part III, we propose new novelties efficient algorithms to solve the PFSP under several objectives. The procedures, constructive and improvement heuristics and metaheuristics, exploit the specific structure of the problem to both reduce the computational times of them and improve the quality of the solutions. Additionally, they are validated in extensive computational evaluations, comparing them with the state-of-the-art algorithms under the same conditions. More specifically, this part is divided in four chapters and addresses the general research objectives GO3 and GO4. Firstly, a new tie-breaking mechanism to minimise makespan, which can be incorporated in the two most efficient algorithms for the problem, is proposed in Chapter 6. In Chapter 7, two efficient constructive heuristics are proposed to minimise total flowtime. Several tie-breaking mechanisms are proposed and compared to minimise total tardiness in Chapter 8. Finally, four procedures to minimise total earliness and tardiness are proposed in Chapter 9. - In Part IV, focused in more real manufacturing environment, new constraints are added to the traditional problem as well as different consideration and interaction between factories are taken into account. The proposed environments are solved using efficient approximate methods taken into consideration ideas of the traditional PFSP. More specifically, an iterated non-population algorithm to minimise makespan subject to a maximum tardiness is proposed in Chapter 10. In the Chapter 11, we add the blocking constraints to the traditional PFSP. These constraints take into consideration limited buffers between the machines. This problem, of permutation nature, is solved by means of an efficient beam-search-based constructive heuristic trying to minimise the total completion time. In Chapter 12, we consider the parallel flowshop scheduling problem also denoted as distributed PFSP where several identical flowshop or even flowshop factories are available in parallel to assign the jobs. The problem is solved using a bounded-search iterated greedy algorithm - Finally, in Part V, the conclusions of this research and future research lines are discussed.Premio Extraordinario de Doctorado U

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available