Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management |
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Authors: | Julius Beneoluchi Odili Mohd Nizam Mohmad Kahar A Noraziah M Zarina Riaz Ul Haq |
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Affiliation: | a Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang, Kuantan, Malaysia;b IBM Centre of Excellence, Universiti Malaysia Pahang, Kuantan, Malaysia;c Faculty of Informatic and Computing, Universiti Sultan Zainal Abidin, Gong Badak, Malaysia |
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Abstract: | This paper carries out a performance analysis of major Nature-inspired Algorithms in solving the
benchmark symmetric and asymmetric Traveling Salesman’s Problems (TSP). Knowledge of the
workings of the TSP is very useful in strategic management as it provides useful guidance to planners.
After critical assessments of the performances of eleven algorithms consisting of two heuristics
(Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s
Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and
seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African
Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and
Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s
optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s
Problems test cases available in TSPLIB91. The study reveals that the African Buffalo Optimization and
the Ant Colony Optimization are the best in solving the symmetric TSP, which is similar to intelligence
gathering channel in the strategic management of big organizations, while the Randomized Insertion
Algorithm holds the best promise in asymmetric TSP instances akin to strategic information exchange
channels in strategic management. |
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Keywords: | Decision-making logistics management natureinspired algorithms performance analysis strategic planning traveling salesman’s problems |
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