Abstract
Traveling Salesman Problem is a well-known NP-Hard problem, which aims at finding the shortest path between numbers of cities. Chemical Reaction Optimization (CRO) is a recently established meta-heuristic algorithm for solving optimization problems which has successfully solved many optimization problems. The main goal of this paper is to investigate the possibility of parallelizing CRO for solving the TSP problem called (PCRO). PCRO is compared with Genetic Algorithm (GA), which is a well-known meta-heuristic algorithm. Experimental results show relatively better performance for PCRO in terms of execution time, Speedup, optimal cost and Error rate.
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Shaheen, A., Sleit, A., Al-Sharaeh, S. (2019). Chemical Reaction Optimization for Traveling Salesman Problem Over a Hypercube Interconnection Network. In: Silhavy, R. (eds) Cybernetics and Algorithms in Intelligent Systems . CSOC2018 2018. Advances in Intelligent Systems and Computing, vol 765. Springer, Cham. https://doi.org/10.1007/978-3-319-91192-2_43
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