Abstract
This paper presents a hypervolume-based multi-objective path relinking algorithm for approximating the Pareto optimal set of multi-objective combinatorial optimization problems. We focus on integrating path relinking techniques within a multi-objective local search as an initialization function. Then, we carry out a range of experiments on bi-objective flow shop problem and bi-objective quadratic assignment problem. Experimental results and a statistical comparison are reported in the paper. In comparison with the other algorithms, one version of our proposed algorithm is very competitive. Some directions for future research are highlighted.
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Zeng, RQ., Basseur, M., Hao, JK. (2013). Hypervolume-Based Multi-Objective Path Relinking Algorithm. In: Purshouse, R.C., Fleming, P.J., Fonseca, C.M., Greco, S., Shaw, J. (eds) Evolutionary Multi-Criterion Optimization. EMO 2013. Lecture Notes in Computer Science, vol 7811. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37140-0_17
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