Prachi Agrawal¹, Khalid Alnowibet², Ali Wagdy Mohamed^3,4,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2847-2868, 2022, DOI:10.32604/cmc.2022.023126

Abstract This paper presents a novel application of metaheuristic algorithms for solving stochastic programming problems using a recently developed gaining sharing knowledge based optimization (GSK) algorithm. The algorithm is based on human behavior in which people gain and share their knowledge with others. Different types of stochastic fractional programming problems are considered in this study. The augmented Lagrangian method (ALM) is used to handle these constrained optimization problems by converting them into unconstrained optimization problems. Three examples from the literature are considered and transformed into their deterministic form using the chance-constrained technique. The transformed problems are solved using GSK algorithm and… More >

Prachi Agrawal¹, Khalid Alnowibet², Talari Ganesh¹, Adel F. Alrasheedi², Hijaz Ahmad³, Ali Wagdy Mohamed^4,5,*

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 817-829, 2022, DOI:10.32604/cmc.2022.019685

Abstract Recent years witness a great deal of interest in artificial intelligence (AI) tools in the area of optimization. AI has developed a large number of tools to solve the most difficult search-and-optimization problems in computer science and operations research. Indeed, metaheuristic-based algorithms are a sub-field of AI. This study presents the use of the metaheuristic algorithm, that is, water cycle algorithm (WCA), in the transportation problem. A stochastic transportation problem is considered in which the parameters supply and demand are considered as random variables that follow the Weibull distribution. Since the parameters are stochastic, the corresponding constraints are probabilistic. They… More >