1. Abstract Swarm algorithms such as Particle Swarm Optimization (PSO) are non-gradient probabilistic optimization algorithms that have been successfully applied to obtain global optimal solutions for complex problems such as multi-peak problems. However these algorithms have not been applied to complicated structural and mechanical optimization problems since local optimization capability is s...

In this article the hybrid optimization algorithm of differential evolution and particle swarm is introduced for designing the fuzzy rule base of a fuzzy controller. For a specific number of rules, a hybrid algorithm for optimizing all open parameters was used to reach maximum accuracy in training. The considered hybrid computational approach includes: opposition-based differential evolution al...

Many heuristic-based approaches have been applied to finding schedules that minimize the execution time of computing tasks on parallel processors. Particle Swarm Optimization is currently employed in several optimization and search problems due its ease and ability to find solutions successfully. A variant of PSO, called as Improved PSO has been developed in this paper and is hybridized with th...

In this paper, the new hybrid particle swarm optimization (hybrid-PSO) based on particle swarm optimization (PSO), evolutionary programming (EP), and tabu search (TS) is developed. Hybrid-PSO is proposed to determine the optimal allocation of multi-type flexible AC transmission system (FACTS) controllers for simultaneously maximizing the power transfer capability of power transactions between g...

Software effort and cost estimation are crucial parts of software project development. It determines the budget, time, resources needed to develop a project. The success development depends mainly on accuracy estimation. A poor will impact result, which worsens management. Various model has been introduced resolve this problem. COnstructive COst MOdel (COCOMO) is well-established model; however...

Group technology (GT) is a useful way to increase productivity with high quality in cellular manufacturing systems (CMSs), in which cell formation (CF) is a key step in the GT philosophy. When boundaries between groups are fuzzy, fuzzy clustering has been successfully adapted to solve the CF problem; however, it may result uneven distribution of parts/machines where the problem becomes larger. ...

This paper presents Chemo-tactic PSO-DE (CPSO-DE) optimization algorithm combined with Lagrange Relaxation method (LR) for solving Unit Commitment (UC) problem. The proposed approach employs Chemo-tactic PSO-DE algorithm for optimal settings of Lagrange multipliers. It provides high-quality performance and reaches global solution and is a hybrid heuristic algorithm based on Bacterial Foraging O...