A multi-objective chemical reaction optimisation algorithm for multi-objective travelling salesman problem. (23rd December 2014)

• Record Type: Journal Article
• Authors: Bouzoubia, Samira; Layeb, Abdesslem; Chikhi, Salim
• Is Part Of: International journal of innovative computing and applications. Volume 6:Number 2(2014)
• Page Start: 87
• Page End: 101
• Publication Date: 2014-12-23
• Subjects: multi-objective chemical reaction -- CRO -- multi-objective optimisation -- bio-inspired algorithm -- multi-objective travelling salesman problem -- MOTSP; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

The multi-objective travelling salesman problem (MOTSP) is a well-known combinatorial optimisation problem that belongs to the class of NP-hard problems. The MOTSP plays an important role in computing theory and in many real life applications. Unfortunately, finding efficient MOTSP solutions is still a challenging problem. That is why several methods were proposed to deal with this problem. This paper proposes a new multi-objective chemical reaction optimisation (MOCRO) algorithm to solve MOTSP. To maintain the diversity of the solutions, MOCRO uses a non-dominated sorting procedure proposed in NSGA2. Two new variants of MOCRO are proposed to deal the MOTSP. The first is MOCRO based on amount of domination (MOCRO-Dom), while the second is MOCRO based on weighted sum (MOCRO-WS). The experimental results have shown the superior performance of MOCRO-Dom and MOCRO-WS compared to NSGA2. Moreover, a comparative study between MOCRO-Dom and MOCRO-WS and the impact of the major parameters on the performance has been investigated.