Flow shop scheduling decisions through Techniques for Order Preference by Similarity to an Ideal Solution (TOPSIS)

The flow-shop scheduling problem (FSP) has been widely studied in the literature and having a very active research area. Over the last few decades, a number of heuristic/meta-heuristic solution techniques have been developed. Some of these techniques offer excellent effectiveness and efficiency at the expense of substantial implementation efforts and being extremely complicated. This paper brings out the application of a Multi-Criteria Decision Making (MCDM) method known as techniques for order preference by similarity to an ideal solution (TOPSIS) using different weighting schemes in flow-shop environment. The objective function is identification of a job sequence which in turn would have minimum makespan (total job completion time). The application of the proposed method to flow shop scheduling is presented and explained with a numerical example. The results of the proposed TOPSIS based technique of FSP are also compared on the basis of some benchmark problems and found compatible with the results obtained from other standard procedures.

[1]  Christos Koulamas,et al.  A new constructive heuristic for the flowshop scheduling problem , 1998, Eur. J. Oper. Res..

[2]  Thomas Sttzle,et al.  Applying iterated local search to the permutation ow shop problem , 1998 .

[3]  E. Nowicki,et al.  A fast tabu search algorithm for the permutation flow-shop problem , 1996 .

[4]  Christian Blum,et al.  Metaheuristics in combinatorial optimization: Overview and conceptual comparison , 2003, CSUR.

[5]  E. Stanley Lee,et al.  An extension of TOPSIS for group decision making , 2007, Math. Comput. Model..

[6]  A. S. Spachis,et al.  Heuristics for flow-shop scheduling , 1980 .

[7]  Stefan Voß,et al.  Solving the continuous flow-shop scheduling problem by metaheuristics , 2003, Eur. J. Oper. Res..

[8]  Ali Allahverdi,et al.  New heuristics for no-wait flowshops to minimize makespan , 2003, Comput. Oper. Res..

[9]  Morteza Yazdani,et al.  A state-of the-art survey of TOPSIS applications , 2012, Expert Syst. Appl..

[10]  Amin Zadeh Sarraf,et al.  Developing TOPSIS method using statistical normalization for selecting knowledge management strategies , 2013 .

[11]  Jacques Carlier,et al.  Ordonnancements à contraintes disjonctives , 1978 .

[12]  R. A. Dudek,et al.  A Heuristic Algorithm for the n Job, m Machine Sequencing Problem , 1970 .

[13]  Jose M. Framiñan,et al.  Approximative procedures for no-wait job shop scheduling , 2003, Oper. Res. Lett..

[14]  Frank Werner,et al.  On the heuristic solution of the permutation flow shop problem by path algorithms , 1993, Comput. Oper. Res..

[15]  Thomas Stützle,et al.  A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem , 2007, Eur. J. Oper. Res..

[16]  Chuen-Lung Chen,et al.  An application of genetic algorithms for flow shop problems , 1995 .

[17]  Teofilo F. Gonzalez,et al.  Flowshop and Jobshop Schedules: Complexity and Approximation , 1978, Oper. Res..

[18]  Sant Ram Chauhan,et al.  A heuristic algorithm for scheduling in a flow shop environment to minimize makespan , 2015 .

[19]  I. Osman,et al.  Simulated annealing for permutation flow-shop scheduling , 1989 .

[20]  D. S. Palmer.  Sequencing Jobs Through a Multi-Stage Process in the Minimum Total Time—A Quick Method of Obtaining a Near Optimum , 1965 .

[21]  Uday K. Chakraborty,et al.  An efficient hybrid heuristic for makespan minimization in permutation flow shop scheduling , 2009 .

[22]  Ching-Lai Hwang,et al.  Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey , 1981, Lecture Notes in Economics and Mathematical Systems.

[23]  Christos D. Tarantilis,et al.  Minimizing makespan in permutation flow shop scheduling problems using a hybrid metaheuristic algorithm , 2009, Comput. Oper. Res..

[24]  Alain Guinet,et al.  Reduction of job-shop problems to flow-shop problems with precedence constraints , 1998, Eur. J. Oper. Res..

[25]  Ling Wang,et al.  An Effective Hybrid Heuristic for Flow Shop Scheduling , 2003 .

[26]  Yeong-Dae Kim,et al.  Heuristics for Flowshop Scheduling Problems Minimizing Mean Tardiness , 1993 .

[27]  Shailendra Kumar,et al.  Development of a cell formation heuristic by considering realistic data using principal component analysis and Taguchi’s method , 2015 .

[28]  G. Rand.  Sequencing and Scheduling: An Introduction to the Mathematics of the Job-Shop , 1982 .

[29]  Mieczysław Wodecki,et al.  A very fast tabu search algorithm for the permutation flow shop problem with makespan criterion , 2004, Comput. Oper. Res..

[30]  C. Hwang.  Multiple Objective Decision Making - Methods and Applications: A State-of-the-Art Survey , 1979 .

[31]  Hong Zhou,et al.  Using Genetic Algorithms and Heuristics for Job Shop Scheduling with Sequence-Dependent Setup Times , 2001, Ann. Oper. Res..

[32]  É. Taillard.  Some efficient heuristic methods for the flow shop sequencing problem , 1990 .

[33]  David G. Dannenbring,et al.  An Evaluation of Flow Shop Sequencing Heuristics , 1977 .

[34]  S. M. Johnson,et al.  Optimal two- and three-stage production schedules with setup times included , 1954 .

[35]  Hamid Davoud Pour.  A new heuristic for the n-job, m-machine flow-shop problem , 2001 .

[36]  Ling Wang,et al.  An effective hybrid optimization strategy for job-shop scheduling problems , 2001, Comput. Oper. Res..

[37]  David L. Olson,et al.  Comparison of weights in TOPSIS models , 2004, Math. Comput. Model..

[38]  Mingyuan Chen,et al.  A mathematical approach for the formation of manufacturing cells , 2005, Comput. Ind. Eng..

[39]  Rubén Ruiz,et al.  TWO NEW ROBUST GENETIC ALGORITHMS FOR THE FLOWSHOP SCHEDULING PROBLEM , 2006 .

[40]  David K. Smith,et al.  The application of the simulated annealing algorithm to the solution of the n/m/Cmax flowshop problem , 1990, Comput. Oper. Res..

[41]  Scott Turner,et al.  Comparison of heuristics for flow shop sequencing , 1987 .

[42]  Inyong Ham,et al.  A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem , 1983 .

[43]  Nasim Nahavandi,et al.  An interactive algorithm for multi-objective flow shop scheduling with fuzzy processing time through resolution method and TOPSIS , 2013 .

[44]  Jung Woo Jung,et al.  Flowshop-scheduling problems with makespan criterion: a review , 2005 .

[45]  Colin R. Reeves,et al.  Improving the Efficiency of Tabu Search for Machine Sequencing Problems , 1993 .

[46]  Rubén Ruiz,et al.  A comprehensive review and evaluation of permutation flowshop heuristics to minimize flowtime , 2013, Comput. Oper. Res..

[47]  Chandrasekharan Rajendran,et al.  Ant-colony algorithms for permutation flowshop scheduling to minimize makespan/total flowtime of jobs , 2004, Eur. J. Oper. Res..

[48]  Colin R. Reeves,et al.  A genetic algorithm for flowshop sequencing , 1995, Comput. Oper. Res..

[49]  Ravi Sethi,et al.  The Complexity of Flowshop and Jobshop Scheduling , 1976, Math. Oper. Res..

[50]  A. Hertz,et al.  A new heuristic method for the flow shop sequencing problem , 1989 .

[51]  Shailendra Kumar,et al.  Cell Formation Heuristic Procedure Considering Production Data , 2014 .

[52]  José María Moreno-Jiménez,et al.  Notes on Dependent Attributes in TOPSIS , 2014, ITQM.