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Multi-Case Multi-Objective Simulated Annealing (MC-MOSA): New Approach to Adapt Simulated Annealing to Multi-objective Optimization
Abstract:In this paper a new approach is proposed for the adaptation of the simulated annealing search in the field of the Multi-Objective Optimization (MOO). This new approach is called Multi-Case Multi-Objective Simulated Annealing (MC-MOSA). It uses some basics of a well-known recent Multi-Objective Simulated Annealing proposed by Ulungu et al., which is referred in the literature as U-MOSA. However, some drawbacks of this algorithm have been found, and are substituted by other ones, especially in the acceptance decision criterion. The MC-MOSA has shown better performance than the U-MOSA in the numerical experiments. This performance is further improved by some other subvariants of the MC-MOSA, such as Fast-annealing MC-MOSA, Re-annealing MCMOSA and the Two-Stage annealing MC-MOSA.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1331259Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1315
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