Solving Engineering Design Problems by Social Cognitive Optimization
نویسندگان
چکیده
Social cognitive optimization (SCO) is a simple behavioral model based on human social cognition. By formalizing the fundamental social cognitive agent, the single-agent and multiagent models of SCO are studied. After realizing the goodness evaluation, the experiments results of SCO are compared with existing results on five engineering design problems, which show that SCO can get high-quality solutions efficiently, even by the single-agent model.
منابع مشابه
FOA: ‘Following’ Optimization Algorithm for solving Power engineering optimization problems
These days randomized-based population optimization algorithms are in wide use in different branches of science such as bioinformatics, chemical physics andpower engineering. An important group of these algorithms is inspired by physical processes or entities’ behavior. A new approach of applying optimization-based social relationships among the members of a community is investigated in this pa...
متن کاملEFFICIENCY OF IMPROVED HARMONY SEARCH ALGORITHM FOR SOLVING ENGINEERING OPTIMIZATION PROBLEMS
Many optimization techniques have been proposed since the inception of engineering optimization in 1960s. Traditional mathematical modeling-based approaches are incompetent to solve the engineering optimization problems, as these problems have complex system that involves large number of design variables as well as equality or inequality constraints. In order to overcome the various difficultie...
متن کاملA Particle Swarm Optimization Algorithm for Mixed-Variable Nonlinear Problems
Many engineering design problems involve a combination of both continuous anddiscrete variables. However, the number of studies scarcely exceeds a few on mixed-variableproblems. In this research Particle Swarm Optimization (PSO) algorithm is employed to solve mixedvariablenonlinear problems. PSO is an efficient method of dealing with nonlinear and non-convexoptimization problems. In this paper,...
متن کاملConstrained Multi-Objective Optimization Problems in Mechanical Engineering Design Using Bees Algorithm
Many real-world search and optimization problems involve inequality and/or equality constraints and are thus posed as constrained optimization problems. In trying to solve constrained optimization problems using classical optimization methods, this paper presents a Multi-Objective Bees Algorithm (MOBA) for solving the multi-objective optimal of mechanical engineering problems design. In the pre...
متن کاملEmergent Social Structures in Cultural Algorithms
Abstract Various biologically inspired approaches to problem solving using a social metaphor have been proposed. For example, both Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) have been employed to solve problems in optimization and design. Both approaches employ simple social interactions between agents to produce emergent social structures that are used to solve a given...
متن کامل