Traveling Transportation Problem Optimization by Adaptive Current Search Method

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Supaporn Suwannarongsri 1,* Tika Bunnag 1 Waraporn Klinbun 2

1. Rattanakosin College for Sustainable Energy and Environment (RCSEE), Rajamangala University of Technology Rattanakosin, Nakhon Pathom, Thailand

2. Faculty of Engineering and Technology, Panyapiwat Institute of Management, Nonthaburi, Thailand

* Corresponding author.


Received: 18 Feb. 2014 / Revised: 15 Mar. 2014 / Accepted: 20 Apr. 2014 / Published: 8 May 2014

Index Terms

Traveling transportation problem, adaptive current search, metaheuristic optimization


The adaptive current search (ACS) is one of the novel metaheuristic optimization search techniques proposed for solving the combinatorial optimization problems. This paper aimed to present the application of the ACS to optimize the real-world traveling transportation problems (TTP) of a specific car factory. The total distance of the selected TTP is performed as the objective function to be minimized in order to decrease the vehicle’s energy. To perform its effectiveness, four real-world TTP problems are conducted. Results obtained by the ACS are compared with those obtained by genetic algorithm (GA), tabu search (TS) and current search (CS). As results, the ACS can provide very satisfactory solutions superior to other algorithms. The minimum total distance and the minimum vehicle’s energy of all TTP problems can be achieved by the ACS with the distant error of no longer than 3.05%.

Cite This Paper

Supaporn Suwannarongsri, Tika Bunnag, Waraporn Klinbun, "Traveling Transportation Problem Optimization by Adaptive Current Search Method", International Journal of Modern Education and Computer Science (IJMECS), vol.6, no.5, pp.33-45, 2014. DOI:10.5815/ijmecs.2014.05.05


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