We present here a co-operative multithread metaheuristic. Each thread employs a (possibly) different optimization strategy and they are controlled by a Coordinator process. A relevant point is the use of a fuzzy rule base embedded in the Coordinator to control and modify the behavior of the optimization threads. Preliminary results over the knapsack problem show the benefits of the proposal.

The present study attempts to apply an efficient yet simple optimization (SOPT) algorithm to optimum design of truss structures under stress and displacement constraints. The computational efficiency of the technique is improved through avoiding unnecessary analyses during the course of optimization using the so-called upper bound strategy (UBS). The efficiency of the UBS integrated SOPT algori...

the traveling salesman problem (tsp) is a well-known combinatorial optimization problem and holds a central place in logistics management. the tsp has received much attention because of its practical applications in industrial problems. many exact, heuristic and metaheuristic approaches have been proposed to solve tsp in recent years. in this paper, a modified ant colony optimization (maco) is ...

Abstract The optimization of dam reservoir operations is the utmost importance, as operators strive to maximize revenue while minimizing expenses, risks, and deficiencies. Metaheuristics have recently been investigated extensively by researchers in management reservoirs. But animal-concept-based metaheuristic algorithm with Lévy flight integration approach has not used at Karun-4. This paper in...

Attempting to address optimization problems in various scientific disciplines is a fundamental and significant difficulty requiring optimization. This study presents the waterwheel plant technique (WWPA), novel stochastic motivated by natural systems. The proposed WWPA’s basic concept based on modeling plant’s behavior while hunting expedition. To find prey, WWPA uses plants as search agents. W...

Risk Budgeted portfolio optimization problem centering on the twin objectives of maximizing expected portfolio return and minimizing portfolio risk and incorporating the risk budgeting investment strategy, turns complex for direct solving by classical methods triggering the need to look for metaheuristic solutions. This work explores the application of an extended Ant Colony Optimization algori...

Metaheuristic algorithms will gain more and more popularity in the future as optimization problems are increasing in size and complexity. In order to record experiences and allow project to be replicated, a standard process as a methodology for designing and implementing metaheuristic algorithms is necessary. To the best of the authors’ knowledge, no methodology has been proposed in literature ...

The area of combinatorial optimization has been enlarged in the recent years into two directions: First, a huge number of articles deals with multiobjective combinatorial optimization (MOCO) problems, for which techniques to determine the set of Pareto-optimal solutions have been developed (cf., e.g., [6], [3]). A major advantage of MOCO approaches is that they are able to provide the decision ...

This paper introduces a framework based on multi-agent system for solving problems of combinatorial optimization. The framework allows running various metaheuristic algorithms simultaneously. By the collaboration of various metaheuristics, we can achieve better results in more classes of problems.