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Multi Expression Programming (MEP) is an evolutionary technique that may beused for solving computationally difficult problems. MEP uses a linear solutionrepresentation. Each MEP individual is a string encoding complex expressions(computer programs). A MEP individual may encode multiple solutions of thecurrent problem. In this paper MEP is used for evolving a Traveling SalesmanProblem (TSP) heuristic for graphs satisfying triangle inequality. Evolved MEPheuristic is compared with Nearest Neighbor Heuristic (NN) and Minimum SpanningTree Heuristic (MST) on some difficult problems in TSPLIB. For most of theconsidered problems the evolved MEP heuristic outperforms NN and MST. Theobtained algorithm was tested against some problems in TSPLIB. The resultsemphasizes that evolved MEP heuristic is a powerful tool for solving difficultTSP instances.

Evolving TSP heuristics using Multi Expression Programming