Sparse experimental design : an effective an efficient way discovering better genetic algorithm structures

The focus of this paper is the demonstration that sparse experimental design is a useful strategy for developing Genetic Algorithms. It is increasingly apparent from a number of reports and papers within a variety of different problem domains that the 'best' structure for a GA may be dependent upon the application. The GA structure is defined as both the types of operators and the parameters settings used during operation. The differences observed may be linked to the nature of the problem, the type of fitness function, or the depth or breadth of the problem under investigation. This paper demonstrates that advanced experimental design may be adopted to increase the understanding of the relationships between the GA structure and the problem domain, facilitating the selection of improved structures with a minimum of effort

An estimation of distribution algorithm for lot-streaming flow shop problems with setup times

Lot-streaming flow shops have important applications in different industries including textile, plastic, chemical, semiconductor and many others. This paper considers an n-job m-machine lot-streaming flow shop scheduling problem with sequence-dependent setup times under both the idling and noidling production cases. The objective is to minimize the maximum completion time or makespan. To solve this important practical problem, a novel estimation of distribution algorithm (EDA) is proposed with a job permutation based representation. In the proposed EDA, an efficient initialization scheme based on the NEH heuristic is presented to construct an initial population with a certain level of quality and diversity. An estimation of a probabilistic model is constructed to direct the algorithm search towards good solutions by taking into account both job permutation and similar blocks of jobs. A simple but effective local search is added to enhance the intensification capability. A diversity controlling mechanism is applied to maintain the diversity of the population. In addition, a speed-up method is presented to reduce the computational effort needed for the local search technique and the NEH-based heuristics. A comparative evaluation is carried out with the best performing algorithms from the literature. The results show that the proposed EDA is very effective in comparison after comprehensive computational and statistical analyses.This research is partially supported by the National Science Foundation of China (60874075, 70871065), and Science Foundation of Shandong Province in China under Grant BS2010DX005, and Postdoctoral Science Foundation of China under Grant 20100480897. Ruben Ruiz is partially funded by the Spanish Ministry of Science and Innovation, under the project "SMPA-Advanced Parallel Multiobjective Sequencing: Practical and Theoretical Advances" with reference DPI2008-03511/DPI and by the IMPIVA-Institute for the Small and Medium Valencian Enterprise, for the project OSC with references IMIDIC/2008/137, IMIDIC/2009/198 and IMIDIC/2010/175.Pan, Q.; Ruiz García, R. (2012). An estimation of distribution algorithm for lot-streaming flow shop problems with setup times. Omega. 40(2):166-180. https://doi.org/10.1016/j.omega.2011.05.002S16618040

Iterated search methods for earliness and tardiness minimization in hybrid flowshops with due windows

[EN] In practice due dates usually behave more like intervals rather than specific points in time. This paper studies hybrid flowshops where jobs, if completed inside a due window, are considered on time. The objective is therefore the minimization of the weighted earliness and tardiness from the due window. This objective has seldom been studied and there are almost no previous works for hybrid flowshops. We present methods based on the simple concepts of iterated greedy and iterated local search. We introduce some novel operators and characteristics, like an optimal idle time insertion procedure and a two stage local search where, in the second stage, a limited local search on a exact representation is carried out. We also present a comprehensive computational campaign, including the reimplementation and comparison of 9 competing procedures. A thorough evaluation of all methods with more than 3000 instances shows that our presented approaches yield superior results which are also demonstrated to be statistically significant. Experiments also show the contribution of the new operators in the presented methods. (C) 2016 Elsevier Ltd. All rights reserved.The authors would like to thank Professors Lofti Hidri and Mohamed Haouari for sharing with us the source codes and explanations of the lower bounds. Quan-Ke Pan is supported by the National Natural Science Foundation of China (Grant No. 51575212), Program for New Century Excellent Talents in University (Grant No. NCET-13-0106), Science Foundation of Hubei Province in China (Grant No. 2015CFB560), Specialized Research Fund for the Doctoral Program of Higher Education (Grant No. 20130042110035), Key Laboratory Basic Research Foundation of Education Department of Liaoning Province (LZ2014014), Open Research Fund Program of the State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, China. Ruben Ruiz and Pedro Alfaro-Fernandez are supported by the Spanish Ministry of Economy and Competitiveness, under the project "SCHEYARD Optimization of Scheduling Problems in Container Yards" (No. DPI2015-65895-R) financed by FEDER funds.Pan, Q.; Ruiz García, R.; Alfaro-Fernandez, P. (2017). Iterated search methods for earliness and tardiness minimization in hybrid flowshops with due windows. Computers & Operations Research. 80:50-60. https://doi.org/10.1016/j.cor.2016.11.022S50608

Interactive approaches to the solution of a class of combinatorial problems

PhD ThesisThis thesis considers the usefulness of interaction between a human and a powerful computer in attempting to solve a class of discrete optimization problems. Some typical problems are described in chapters 1 and 2 and the effectiveness of their exact solution by existing methods is assessed. Chapter 3 presents some heuristic techniques which produce good approximate solutions and the value of such methods is discussed. An alternative approach, that of providing a mechanism for manmachine interaction is proposed in chapter 4. A system for providing easy access to a range of algorithmic and heuristic techniques is described. The system, named IMPACT, was implemented by the author and its many features include the interruption, interrogation, adjustment and resumption of a process or algorithm. Some novel interactive tree-manipulation techniques and their usage are introduced in chapter 5. This chapter also describes extensions to certain other heuristics in order to improve their power when used interactively. Throughout the thesis a job-shop scheduling problem serves as a useful vehicle for illustrating ideas. This problem was investigated extensively and chapter 6 is devoted to the topic. The idea of a critical path of jobs through machines is introduced together with the slack time of a job upon a machine under a particular schedule. Branch-and-bound approaches to the problem have been proposed in the past. The performance of such an approach has been substantially improved, as is shown by new results. The improvement stems from two sources both of which were discovered interactively; i) a different branching procedure designed to exploit features of the job-shop scheduling problem, and ii) more realistic lower bounds than those originally proposed. The final chapter discusses the generality of the approach and illustrates the extendability of IMPACT. Other discrete optimization problems are discussed briefly and a branch-andbound formulation to one of them, an assignment problem~ is presented. An interactive approach by other authors to the travelling salesman problem is reviewed and features similar to those experienced in the job-shop scheduling investigation are remarked upon. To conclude, the advantages to be gained from an interactive approach are discussed

A strategy for modelling the design-development phase of a product

PhD ThesisThis thesis describes a strategy for modelling the design-development phase of a product. Specifically, the aim is to provide product development organisations with a strategy for modelling and optimising sequences and schedules of design-development activities such that this phase of a product's life cycle can be managed and controlled in a more effective manner than before. This helps to ensure that product cost can be minimised, product quality can be maximised and the product's time to market can be reduced. The proposed strategy involves carrying out five strategic functions, namely; (1) create a product design-work breakdown structure of design-development activities; (2) model the activities and their data-dependencies; (3) derive a near optimal sequence of activities; (4) derive an activity network diagram; and, (5) derive a resource-constrained schedule of activities. The five strategic functions involve the use of a number of modelling and optimisation techniques. In particular, the thesis describes; (i) an enhanced version of a matrix-based modelling technique, namely the design structure matrix (DSM), which is used to model design-development activities and their data-dependencies; (ii) a newly created optimisation search procedure which combines a genetic algorithm with a heuristic-based local search to derive a near optimal sequence of activities; (iii) a newly created procedure which, based on the resolution of a matrix-model of activities linked by their mutual dependence on one another for data, is used to derive an activity network diagram of activities and precedence relationships; and, (iv) the development of a multiple-criteria genetic algorithm which is used to derive a near optimal resource-constrained schedule of activities. Near optimal sequences are derived using objectives such as minimising iteration and maximising concurrency whilst near optimal schedules are derived using objectives such as minimising the time taken to complete all activities and maximising the utilisation of scarce resources. At the same time, throughout the thesis, a number of related concepts are discussed and developed. In particular, the thesis addresses concurrent engineering, a systems approach to business processes and design reuse. In order to demonstrate how the modelling strategy can be applied, an industrial case study based on the design-development of a warship has been included.EPSRC: Newcastle Engineering Design Centre

A hybrid genetic approach to solve real make-to-order job shop scheduling problems

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro TecnologicoProcedimentos de busca local (ex. busca tabu) e algoritmos genéticos têm apresentado excelentes resultados em problemas clássicos de programação da produção em ambientes job shop. No entanto, estas abordagens apresentam pobres habilidades de modelamento e poucas aplicações com restrições de ambientes reais de produção têm sido publicadas. Além disto, os espaços de busca considerados nestas aplicações são nomlalmente incompletos e as restrições reais são poucas e dependentes do problema em questão. Este trabalho apresenta uma abordagem genética híbrida para resolver problemas de programação em ambientes job shop com grande número de restrições reais, tais como produtos com vários níveis de submontagem, planos de processamento altemativos para componentes e recursos alternativos para operações, exigência de vários recursos para executar uma operação (ex., máquina, ferramentas, operadores), calendários para todos os recursos, sobreposição de operações, restrições de disponibilidade de matéria-prima e componentes comprados de terceiros, e tempo de setup dependente da sequência de operações. A abordagem também considera funções de avaliação multiobjetivas. O sistema usa algoritmos modificados de geração de programação, que incorporam várias heurísticas de apoio à decisão, para obter um conjunto de soluções iniciais. Cada solução inicial é melhorada por um algoritmo de subida de encosta. Então, um algoritmo genético híbrido com procedimentos de busca local é aplicado ao conjunto inicial de soluções localmente ótimas. Ao utilizar técnicas de programação de alta perfomlance (heurísticas construtivas, procedimentos de busca local e algoritmos genéticos) em problemas reais de programação da produção, este trabalho reduziu o abismo existente entre a teoria e a prática da programação da produção

Algorithms for Scheduling Problems

This edited book presents new results in the area of algorithm development for different types of scheduling problems. In eleven chapters, algorithms for single machine problems, flow-shop and job-shop scheduling problems (including their hybrid (flexible) variants), the resource-constrained project scheduling problem, scheduling problems in complex manufacturing systems and supply chains, and workflow scheduling problems are given. The chapters address such subjects as insertion heuristics for energy-efficient scheduling, the re-scheduling of train traffic in real time, control algorithms for short-term scheduling in manufacturing systems, bi-objective optimization of tortilla production, scheduling problems with uncertain (interval) processing times, workflow scheduling for digital signal processor (DSP) clusters, and many more

Genetic based discrete particle swarm optimization for elderly day care center timetabling

The timetabling problem of local Elderly Day Care Centers (EDCCs) is formulated into a weighted maximum constraint satisfaction problem (Max-CSP) in this study. The EDCC timetabling problem is a multi-dimensional assignment problem, where users (elderly) are required to perform activities that require different venues and timeslots, depending on operational constraints. These constraints are categorized into two: hard constraints, which must be fulfilled strictly, and soft constraints, which may be violated but with a penalty. Numerous methods have been successfully applied to the weighted Max-CSP; these methods include exact algorithms based on branch and bound techniques, and approximation methods based on repair heuristics, such as the min-conflict heuristic. This study aims to explore the potential of evolutionary algorithms by proposing a genetic-based discrete particle swarm optimization (GDPSO) to solve the EDCC timetabling problem. The proposed method is compared with the min-conflict random-walk algorithm (MCRW), Tabu search (TS), standard particle swarm optimization (SPSO), and a guided genetic algorithm (GGA). Computational evidence shows that GDPSO significantly outperforms the other algorithms in terms of solution quality and efficiency

Iterated Greedy methods for the distributed permutation flowshop scheduling problem

[EN] Large manufacturing firms operate more than one production center. As a result, in relation to scheduling problems, which factory manufactures which product is an important consideration. In this paper we study an extension of the well known permutation flowshop scheduling problem in which there is a set of identical factories, each one with a flowshop structure. The objective is to minimize the maximum completion time or makespan among all factories. The resulting problem is known as the distributed permutation flowshop and has attracted considerable interest over the last few years. Contrary to the recent trend in the scheduling literature, where complex nature-inspired or metaphor-based methods are often proposed, we present simple Iterated Greedy algorithms that have performed well in related problems. Improved initialization, construction and destruction procedures, along with a local search with a strong intensification are proposed. The result is a very effective algorithm with little problem-specific knowledge that is shown to provide demonstrably better solutions in a comprehensive and thorough computational and statistical campaign.Ruben Ruiz is partially supported by the Spanish Ministry of Economy and Competitiveness, under the project "SCHEYARD - Optimization of Scheduling Problems in Container Yards" (No. DPI2015-65895-R) financed by FEDER funds. Quan-Ke Pan is supported by the National Natural Science Foundation of China (Grant No. 51575212).Ruiz García, R.; Pan, Q.; Naderi, B. (2019). Iterated Greedy methods for the distributed permutation flowshop scheduling problem. Omega. 83:213-222. https://doi.org/10.1016/j.omega.2018.03.004S2132228