This paper applies the Evolutionary Strategy (ES) metaheuristic to the automatic test data generation problem. The problem consists in creating automatically a set of input data to test a program. This is a required step in software development and a time consuming task in all software companies. We describe our proposal and study the influence of some parameters of the algorithm in the results...

This paper presents a Multi-MetaHeuristic combined Ant Colony System (ACS)-Travelling Salesman Problem(TSP) algorithm for solving the TSP. We introduce genetic algorithm in ACS-TSP to search solutions space for dealing with the early stagnation problem of the traveling salesman problem. Moreover, we present a new strategy of Minimum Spanning Tree (MST) coupled with Nearest Neighbor(NN) to const...

As a general branch of project scheduling problems, resource investment problem (RIP) considers resource availabilities as decision variables to determine a level of employed resources minimizing the costs of the project. In addition to costs (cash outflows), researchers in the later extensions of the RIP took payments (cash inflows) received from clients into account and used the net present v...

Due to the fact that the error surface of adaptive infinite impulse response (IIR) systems is generally nonlinear and multimodal, the conventional derivative based techniques fail when used in adaptive identification of such systems. In this case, global optimization techniques are required in order to avoid the local minima. Harmony search (HS), a musical inspired metaheuristic, is a recently ...

arguably, the natural gas transmission pipeline infrastructure in iran represents one of the largest andmost complex mechanical systems in the world. the optimization of large gas trunk lines known asigat results in reduced fuel consumption or higher capability and improves pipeline operation. in thecurrent study, a single-objective optimization was conducted for khormoj compressor station on t...

Developing metaheuristics requires in general a lot of work tuning different parameters. This paper presents a two–level algorithm to tackle this problem: an upper–level algorithm is used to determine the most appropriate set of parameters for a lower–level metaheuristic. This approach is applied to an Ant Colony Optimisation (ACO) metaheuristic that was designed to solve the Orienteering Probl...

This paper proposes a bi-objective model for the facility location problem under a congestion system. The idea of the model is motivated by applications of locating servers in bank automated teller machines (ATMS), communication networks, and so on. This model can be specifically considered for situations in which fixed service facilities are congested by stochastic demand within queueing frame...

This paper deals with the Permutation Flow Shop scheduling problem with the objective of minimizing total flow time, and therefore reducing in-process inventory. A new hybrid metaheuristic Genetic Algorithm Cluster Search is proposed for the scheduling problem solution. The performance of the proposed method is evaluated and results are compared with the best reported in the literature. Experim...