Harmony Search (HS) is a phenomenon-mimicking algorithm a metaheuristic inspired by the improvisation process of musicians proposed by Zong Woo Geem (2001). Multiobjective, Multiconstratined optimization for determining the Global Optima from several Local Optima is challenging and toughest task, which can be strategically solved by HS metaheuristic algorithm. The capability of the improvisatio...

Diversification-Based Learning (DBL) derives from a collection of principles and methods introduced in the field of metaheuristics that have broad applications in computing and optimization. We show that the DBL framework goes significantly beyond that of the more recent Opposition-based learning (OBL) framework introduced in Tizhoosh (2005), which has become the focus of numerous research init...

We propose a new nature inspired metaheuristic approach based on the V flight formation of the migrating birds which is proven to be an effective formation in energy saving. Its performance is tested on quadratic assignment problem instances arising from a real life problem and very good results are obtained. The quality of the solutions we report are better than simulated annealing, tabu searc...

Abstract The Social Golfer Problem (SGP) is a combinatorial optimization problem that exhibits a lot of symmetry and has recently attracted significant attention. In this paper, we present a new greedy heuristic for the SGP, based on the intuitive concept of freedom among players. We use this heuristic in a complete backtracking search, and match the best current results of constraint solvers f...

There is a growing research activity around the use of metaheuristic search techniques (e.g., genetic algorithms) in software engineering, for example to support test case generation. This is often referred to as search-based software engineering and is the subject of an international conference every year. This presentation will reflect on several years of research, involving several collabora...

Metaheuristic optimization algorithms have become popular choice for solving complex and intricate problems which are otherwise difficult to solve by traditional methods. In the present study an attempt is made to review the hybrid optimization techniques in which one main algorithm is a well known metaheuristic; particle swarm optimization or PSO. Hybridization is a method of combining two (or...

The paper describes the proposition and application of a local search metaheuristic for multi-objective optimization problems. It is based on two main principles of heuristic search, intensification through variable neighborhoods, and diversification through perturbations and successive iterations in favorable regions of the search space. The concept is successfully tested on permutation flow s...

The capacitated single assignment hub location problem with modular link capacities is a variant of the classical hub location problem in which the cost of using edges is not linear but stepwise, and the hubs are restricted in terms of transit capacity rather than in the incoming traffic. This problem was introduced by Yaman and Carello in [18] and treated by a branch-and-cut and a tabu search ...

We study the Mixed Capacitated General Routing Problem (MCGRP) in which a fleet of capacitated vehicles has to serve a set of requests by traversing a mixed weighted graph. The requests may be located on nodes, edges, and arcs. The problem has theoretical interest because it is a generalization of the Capacitated Vehicle Routing Problem (CVRP), the Capacitated Arc Routing Problem (CARP), and th...