Please use this identifier to cite or link to this item: https://doi.org/10.1109/CEC.2012.6256438
Title: A hybrid estimation of distribution algorithm for solving the multi-objective multiple traveling salesman problem
Authors: Shim, V.A.
Tan, K.C. 
Tan, K.K. 
Keywords: Decomposition
estimation of distribution algorithm
evolutionary gradient search
hybrid multi-objective optimization
multiple traveling salesman problem
restricted Boltzmann machine
Issue Date: 2012
Source: Shim, V.A.,Tan, K.C.,Tan, K.K. (2012). A hybrid estimation of distribution algorithm for solving the multi-objective multiple traveling salesman problem. 2012 IEEE Congress on Evolutionary Computation, CEC 2012 : -. ScholarBank@NUS Repository. https://doi.org/10.1109/CEC.2012.6256438
Abstract: The multi-objective multiple traveling salesman problem (MmTSP) is a generalization of the classical multi-objective traveling salesman problem. In this paper, a formulation of the MmTSP, which considers the weighted sum of the total traveling costs of all salesmen and the highest traveling cost of any single salesman, is proposed. An estimation of distribution algorithm (EDA) based on restricted Boltzmann machine is used for solving the formulated problem. The EDA is developed in the decomposition framework of multi-objective optimization. Due to the limitation of EDAs in generating a wide range of solutions, the EDA is hybridized with the evolutionary gradient search. Simulation studies are carried out to examine the optimization performances of the proposed algorithm on MmTSP with different number of objective functions, salesmen and problem sizes. © 2012 IEEE.
Source Title: 2012 IEEE Congress on Evolutionary Computation, CEC 2012
URI: http://scholarbank.nus.edu.sg/handle/10635/68838
ISBN: 9781467315098
DOI: 10.1109/CEC.2012.6256438
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