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A Learning based Algorithm for Traveling Salesman Problem  

Lim, JoonMook (Department of Industrial and Management Engineering, Hanbat National University)
Bae, SungMin (Department of Industrial and Management Engineering, Hanbat National University)
Suh, JaeJoon (Department of Industrial and Management Engineering, Hanbat National University)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.32, no.1, 2006 , pp. 61-73 More about this Journal
Abstract
This paper deals with traveling salesman problem(TSP) with the stochastic travel time. Practically, the travel time between demand points changes according to day and time zone because of traffic interference and jam. Since the almost pervious studies focus on TSP with the deterministic travel time, it is difficult to apply those results to logistics problem directly. But many logistics problems are strongly related with stochastic situation such as stochastic travel time. We need to develop the efficient solution method for the TSP with stochastic travel time. From the previous researches, we know that Q-learning technique gives us to deal with stochastic environment and neural network also enables us to calculate the Q-value of Q-learning algorithm. In this paper, we suggest an algorithm for TSP with the stochastic travel time integrating Q-learning and neural network. And we evaluate the validity of the algorithm through computational experiments. From the simulation results, we conclude that a new route obtained from the suggested algorithm gives relatively more reliable travel time in the logistics situation with stochastic travel time.
Keywords
TSP; stochastic travel time; q-learning; neural network;
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