TY - JOUR ID - TI - Single-based and Population-based Metaheuristics for Solving NP-hard Problems AU - Saman M. Almufti1* AU - Ridwan B. Marqas2 AU - Pawan Sh. Othman3 AU - Amira Bibo Sallow4 PY - 2021 VL - 62 IS - 5 SP - 1710 EP - 1720 JO - Iraqi Journal of Science المجلة العراقية للعلوم SN - 00672904 23121637 AB - Metaheuristic is one of the most well-known fields of research used to find optimum solutions for non-deterministic polynomial hard (NP-hard) problems, for which it is difficult to find an optimal solution in a polynomial time. This paper introduces the metaheuristic-based algorithms and their classifications and non-deterministic polynomial hard problems. It also compares the performance of two metaheuristic-based algorithms (Elephant Herding Optimization algorithm and Tabu Search) to solve the Traveling Salesman Problem (TSP), which is one of the most known non-deterministic polynomial hard problems and widely used in the performance evaluations for different metaheuristics-based optimization algorithms. The experimental results of Elephant Herding Optimization algorithm and Tabu Search for solving ten different problems from the TSPLIB95 library are compared.

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