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This paper presents and experiments approaches to solve a new bi-objective routing problem called the ring star problem. It consists of locating a simple cycle through a subset of nodes of a graph while optimizing two kinds of cost. The first objective is the minimization of a ring cost that is related to the length of the cycle. The second one is the minimization of an assignment cost from non-visited nodes to visited ones. In spite of its obvious bi-objective formulation, this problem has<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/0804.3965v2">arXiv:0804.3965v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lv7ulxaqejhafm4tdlkw5bqjii">fatcat:lv7ulxaqejhafm4tdlkw5bqjii</a> </span>
more »... ys been investigated in a single-objective way. To tackle the bi-objective ring star problem, we first investigate different stand-alone search methods. Then, we propose two cooperative strategies that combines two multiple objective metaheuristics: an elitist evolutionary algorithm and a population-based local search. We apply this new hybrid approaches to well-known benchmark test instances and demonstrate their effectiveness in comparison to non-hybrid algorithms and to state-of-the-art methods.
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