A Bender’s Algorithm of Decomposition Used for the Parallel Machine Problem of Robotic Cell

Mohammad Reza Komari Alaei, Mehmet Soysal, Atabak Elmi, Audrius Banaitis, Nerija Banaitiene, Reza Rostamzadeh and Shima Javanmard
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Mohammad Reza Komari Alaei: Department of Business Administration, Hacettepe University, 06800 Beytepe, Ankara, Turkey
Mehmet Soysal: Department of Business Administration, Hacettepe University, 06800 Beytepe, Ankara, Turkey
Atabak Elmi: School of Information Technology, Deakin University, Geelong, VIC 3220, Australia
Audrius Banaitis: Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, 10223 Vilnius, Lithuania
Nerija Banaitiene: Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, 10223 Vilnius, Lithuania
Reza Rostamzadeh: Department of Management, Urmia Branch, Islamic Azad University, Urmia, Iran
Shima Javanmard: Department of Industrial Engineering, Eqbal Lahoori Institute of Higher Education, Mashhad, Iran

Mathematics, 2021, vol. 9, issue 15, 1-15

Abstract: The present research addresses the single transportation robot used to alleviate problems of robotic cell scheduling of the machines. For the purpose of minimizing the make-span, a model of mixed-integer linear programming (MILP) has been suggested. Since the inefficiency exists in NP-hard, a decomposition algorithm posed by Bender was utilized to alleviate the problem in real life situations. The proposed algorithm can be regarded as an efficient attempt to apply optimality Bender’s cuts regarding the problem of parallel machine robotic cell scheduling in order to reach precise resolutions for medium and big sized examples. The numerical analyses have demonstrated the efficiency of the proposed solving approach.

Keywords: parallel machine; robotic cell scheduling problem (CSP); mixed integer linear programming (MILP); Benders’ decomposition method; logic-based Benders’ decomposition (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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