Research Article Open Access

Traveling Salesman Approach for Solving Petrol Distribution Using Simulated Annealing

  • Zuhaimy Ismail
  • Wan Rohaizad Wan Ibrahim

American Journal of Applied Sciences
Volume 5 No. 11, 2008, 1543-1546
DOI: https://doi.org/10.3844/ajassp.2008.1543.1546

Abstract

This research presents an attempt to solve a logistic company's problem of delivering petrol to petrol station in the state of Johor. This delivery system is formulated as a travelling salesman problem (TSP). TSP involves finding an optimal route for visiting stations and returning to point of origin, where the inter-station distance is symmetric and known. This real world application is a deceptive simple combinatorial problem and our approach is to develop solutions based on the idea of local search and meta-heuristics. As a standard problem, we have chosen a solution is a deceptively simple combinatorial problem and we defined it simply as the time spends or distance travelled by salesman visiting n cities (or nodes) cyclically. In one tour the vehicle visits each station just once and finishes up where he started. As standard problems, we have chosen TSP with different stations visited once. This research presents the development of solution engine based on local search method known as Greedy Method and with the result generated as the initial solution, Simulated Annealing (SA) and Tabu Search (TS) further used to improve the search and provide the best solution. A user friendly optimization program developed using Microsoft C++ to solve the TSP and provides solutions to future TSP which may be classified into daily or advanced management and engineering problems.

How to Cite

Ismail, Z. & Ibrahim, W. R. W. (2008). Traveling Salesman Approach for Solving Petrol Distribution Using Simulated Annealing . American Journal of Applied Sciences, 5(11), 1543-1546. https://doi.org/10.3844/ajassp.2008.1543.1546

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Keywords

  • Heuristic method
  • tabu search
  • simulated annealing
  • travelling salesman problem and greedy search