Application of Discrete Whale Optimization Hybrid Algorithm in Multiple Travelling Salesmen Problem

Adaptive Grey Wolf Optimization Algorithm with Neighborhood Search Operations: An Application for Traveling Salesman Problem

“…Although the algorithm produced promising results, it has limitations in maintaining quality when feeding back the algorithm to find more solutions in the neighborhood. Other hybrid algorithm proposed discrete whale optimization (DWO) with ACO algorithm to improve the performance of DWO [47]. The initialization of individuals improved by the ACO algorithm as the initial phase of DWO algorithms.…”

“…The TSP instance used in the second scenario, as shown in Table 1, belongs to the standard library and is selected to test eil76, eli51, berlin52, kroa100, st70, oliver30, pr76, pr107, ch150, d198, tsp225, and f1417. The algorithms used in the second scenario are discrete whale optimization algorithm (DWOA) [47], discrete whale optimization algorithm with variable neighborhood search (VDWOA) [48], bat algorithm (BA) [59], GWO, moth-flame optimization (MFO) [60], and PSO [61]. In this scenario, each algorithm is performed 50 times, and the optimal solution provided is used in the comparison.…”