Traveling Transportation Problem Optimization by Adaptive Current Search Method

Abstract

Abstract-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%.

Construction and Management of Cold Chain Logistics of Maritime Silk Route

“…The whole process of maritime transportation includes five basic links: delivery, ground transportation, waterway transportation, arrival service and receipt [15]. There are three main bodies involved: shipper, carrier and consignee [16].…”

Application of Intensified Current Search to Multiobjective PID Controller Optimization

“…The ACS possesses the memory list (ML) and the adaptive radius (AR) mechanism to speed up the search process. The ACS was satisfactory applied to assembly line balancing problems [23,24] and transportation problems [25]. Although both CS and ACS performed good performance, their applications are limited by single-objective optimization problems.…”