Many problems that we face nowadays can be expressed as optimization problems. Finding the best solution for real-world instances of such problems is hard or even infeasible. Metaheuristic algorithms have been used for decades to guide the search for satisfactory solutions in hard optimization problems at an affordable cost. However, despite its many benefits, the application of metaheuristics ...

This study presents a new approach based on Tanaka's fuzzy linear regression (FLP) algorithm to solve well-known power system economic load dispatch problem (ELD). Tanaka's fuzzy linear regression (FLP) formulation will be employed to compute the optimal solution of optimization problem after linearization. The unknowns are expressed as fuzzy numbers with a triangular membership function that h...

The Graph Coloring Problem (GCP) is one of the most interesting, studied, and difficult combinatorial optimization problems. That is why several approaches were developed for solving this problem, including exact approaches, heuristic approaches, metaheuristics, and hybrid approaches. This paper tries to solve the graph coloring problem using a discrete binary version of cuckoo search algorithm...

The topic of simulation–optimization has not been fundamentally tackled by many continuous-time modeling and simulation tools, yet. Common simulation-based optimization problems are usually coupled with standard optimization algorithms like any other simulation-free nonlinear optimization problems. While such couplings are usually based on many state-of-the-art software engineering concepts wit...

Nature inspired metaheuristics proved to be very successful when applied to hard optimization problems, combinatorial as well as global. For all these algorithms, with very different basic ideas, parameters and implementation details, the common problem that ultimately determines the successfulness of a particular algorithm is balance between exploitation and exploration. Exploitation refers to...

We consider a combination of the capacitated vehicle routing problem and a class of additional loading constraints involving a parallel machine scheduling problem. The work is motivated by a real-world transportation problem occurring to a wood-products retailer, which delivers its products to a number of customers in a specific region. We solve the problem by means of two different metaheurist...

J. Deon Garrett. Ph.D. The University of Memphis. February, 2008. Multiobjective Fitness Landscape Analysis and the Design of Effective Memetic Algorithms. Major Professor: Dipankar Dasgupta, Ph.D. For a wide variety of combinatorial optimization problems, no efficient algorithms exist to exactly solve the problem unless P=NP. For these problems, metaheuristics have come to dominate the landsca...

In the past few decades, metaheuristics have demonstrated their suitability in addressing complex problems over different domains. This success drives scientific community towards definition of new and better-performing heuristics results an increased interest this research field. Nevertheless, studies been focused on developing algorithms without providing consolidation existing knowledge. Fur...