A sequence dependent single machine scheduling problem with fuzzy axiomatic design for the penalty costs

• Published in: Computers & industrial engineering Vol. 92; pp. 95 - 104
• Main Authors: Kır, Sena, Yazgan, Harun Reşit
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.02.2016; Pergamon Press Inc
• Subjects: Algorithms; Cost reduction; Costs; Food industry; Fuzzy; Fuzzy axiomatic design; Fuzzy set theory; Genetic algorithm; Genetic algorithms; Heuristic; Job shops; Just in time; Mathematical models; Production scheduling; Schedules; Scheduling; Sequence dependent setup time; Single machine scheduling; Studies; Tabu search algorithm; Sequence dependent setup time; Fuzzy axiomatic design; Genetic algorithm; Food industry; Single machine scheduling; Tabu search algorithm
• ISSN: 0360-8352; 1879-0550
• DOI: 10.1016/j.cie.2015.12.012

•Applicability of the schedules was raised using FAD.•The FAD technique enables to take into account the experiences of scheduling experts.•We proposed an approach for a real life problem that cannot be modelled mathematically.•We employed the approach for the problem with 4.7% heuristic error. In this paper, a scheduling problem on a single machine producing dairy products subject to variable due dates, earliness and tardiness penalty costs and sequence dependent setup times was studied. The main purpose was to meet demands of customers just in time whilst total penalty costs of earliness and tardiness were minimized. In addition, applicability of the schedules was appraised using Fuzzy Axiomatic Design (FAD) to determine earliness and tardiness penalty costs. A hierarchical approach consisting of meta-heuristic algorithms such as a tabu search and a genetic algorithm was proposed to generate proper schedules. In the first stage, an initial solution was found by the tabu search algorithm. The solution was improved using the genetic algorithm to find an optimum or a near optimum solution in the second stage. The proposed approach was employed on a cheese production process in the food industry. An instance of the algorithm was demonstrated to illustrate the applicability of the proposed approach and the results obtained were highly favourable.