Application of the cohort-intelligence optimization method to three selected combinatorial optimization problems

Anand J. Kulkarni, M.F. Baki and Ben A. Chaouch

European Journal of Operational Research, 2016, vol. 250, issue 2, 427-447

Abstract: The real world problems in the supply-chain domain are generally constrained and combinatorial in nature. Several nature-/bio-/socio-inspired metaheuristic methods have been proposed so far solving such problems. An emerging metaheuristic methodology referred to as Cohort Intelligence (CI) in the socio-inspired optimization domain is applied in order to solve three selected combinatorial optimization problems. The problems considered include a new variant of the assignment problem which has applications in healthcare and inventory management, a sea-cargo mix problem and a cross-border shipper selection problem. In each case, we use two benchmarks for evaluating the effectiveness of the CI method in identifying optimal solutions. To assess the quality of solutions obtained by using CI, we do comparative testing of its performance against solutions generated by using CPLEX. Furthermore, we also compare the performance of the CI method to that of specialized multi-random-start local search optimization methods that can be used to find solutions to these problems. The results are robust with a reasonable computational time and accuracy.

Keywords: Cohort intelligence; Combinatorial problems; Assignment problem; Cross-border shipper selection problem; Sea-Cargo mix problem (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:250:y:2016:i:2:p:427-447

DOI: 10.1016/j.ejor.2015.10.008

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