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An evolutionary approach to generalized biobjective traveling salesperson problem
Affiliation:1. University of Vienna, Department of Business Administration, Oskar-Morgenstern-Platz 1, Vienna 1090, Austria;2. Austrian Institute of Technology, Mobility Department - Dynamic Transportation Systems, Giefinggasse 2, Vienna 1210, Austria;3. University of Vienna, Department of Statistics and Operations Research, Oskar-Morgenstern-Platz 1, Vienna 1090, Austria
Abstract:We consider the generalized biobjective traveling salesperson problem, where there are a number of nodes to be visited and each node pair is connected by a set of edges. The final route requires finding the order in which the nodes are visited (tours) and finding edges to follow between the consecutive nodes of the tour. We exploit the characteristics of the problem to develop an evolutionary algorithm for generating an approximation of nondominated points. For this, we approximate the efficient tours using approximate representations of the efficient edges between node pairs in the objective function space. We test the algorithm on several randomly-generated problem instances and our experiments show that the evolutionary algorithm approximates the nondominated set well.
Keywords:Evolutionary computations  Multiobjective decision making  Combinatorial optimization  Multiobjective traveling salesperson problem
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