Walk-Spread Algorithm: A Fast and Superior Stochastic Optimization
Purba Daru Kusuma, Anggunmeka Luhur Prasasti, F Zeidabadi, M Dehghani, O Malik, H Dakheel, Z Abdullah, S Shneen, M Zadehbagheri, T Sutikno, M Kiani, M Yousefi, Y Zahraoui, I Alhamrouni, S Mekhilef, T Kortko, A Jusoh, T Sutikno, G Kishore, P Sekhar, B Soualah, A Chemsa, R Ajgou, H Bella, V Sanjeevulu, D Sunaryono, J Siswantoro, A Raharjo, R Ridho, R Sarno, S Sabilla, R Susilo, H Praveena, C Subhas, K Naidu, A Elnawasany, M Makhlouf, B Tawfik, H Nassar, M Dehghani, S Hubalovsky, P Trojovksy, E Trojovska, M Dehghani, M Braik, M Akbari, M Zare, R Abarghooee, S Mirjalili, M Deriche, M Dehghani, Z Montazeri, E Trojovska, P Trojovsky, E Trojovska, M Dehghani, P Trojovsky, E Trojovska, M Dehghani, P Trojovsky, N Chopra, M Ansari, A Suyanto, A Ariyanto, Ariyanto, P Coufal, S Hubalovsky, M Hubalovska, Z Balogh, M Dehghani, S Hubalovsky, P Trojovsky, M Dehghani, P Trojovsky, P Trojovsky, M Dehghani, D Polap, M Wozniak, L Abualigah, M Elaziz, P Sumari, Z Geem, A Gandomi, M Suman, V Sakthivel, P Sathya, M Dehghani, S Hubalovsky, P Trojovsky, F Zeidabadi, S Doumari, M Dehghani, O Malik, M Dehghani, Z Montazeri, A Dehghani, R Mendoza, H Samet, J Guerrero, G Dhiman
Abstract
This work offers a new stochastic optimization i.e., a metaheuristic algorithm combining both directionbased search and neighbourhood search called as walk-spread algorithm (WSA).These two types of searches become the inspiration for its name where the term walk represents the direction-based search while the term spread represents the neighbourhood search.There are two direction-based searches performed in every iteration where each search produces a single child.Meanwhile, there are two neighbourhood searches performed in every iteration where each search produces several children.The global best unit becomes the first reference while two shuffled units become the second reference in performing the direction-based search.Meanwhile, the local search space of the first neighbourhood search is wide while the second one is narrow.The 23 classic functions are chosen as the assessment of WSA where WSA is confronted with the five latest metaheuristics: mixed leader-based optimization (MLBO), golden search optimization (GSO), pelican optimization algorithm (POA), zebra optimization algorithm (ZOA), and attack-leave optimization (ALO).The assessment result shows that the offered WSA achieves the acceptable result so fast.Moreover, WSA is also superior to these five confronters by outperforming MLBO, GSO, POA, ZOA, and ALO in 23,23,22,21, and 21 functions respectively.