Genetic algorithms have attracted a good deal of interest in the heuristic search community. Yet there are several diierent types of genetic algorithms with varying performance and search characteristics. In this paper we look at 3 genetic algorithms: an elitist simple genetic algorithm, the CHC algorithm and Genitor. One problem in comparing algorithms is that most test problems in the genetic...

This paper presents an exact algorithm, a constructive heuristic algorithm, and a metaheuristic for the Hamiltonian p-Median Problem (HpMP). The exact algorithm is a branch-and-cut algorithm based on an enhanced p -median based formulation, which is proved to dominate an existing p -median based formulation. The constructive heuristic is a giant tour heuristic, based on a dynamic programming fo...

This paper experimentally investigates the dynamical behavior of a search process in a local heuristic search system for a combinatorial optimization problem. Or-opt heuristic algorithm is chosen as the study subject, and the well-known traveling salesman problem (TSP) serves as a problem testbed. This study constructs the search trajectory by using the time-delay method, evaluates the dynamics...

This paper investigates two different local search approaches for the TSP. Both approaches are based on the general concept of single-alternating cycle neighborhoods. The first approach, stems from the famous heuristic suggested by Lin and Kernighan and the second is based on the notion of stemand-cycles developed by Glover in the early nineties. We show that the corresponding neighborhoods are...

This paper extends a recently proposed model for combinatorial landscapes: Local Optima Networks (LON), to incorporate a first-improvement (greedyascent) hill-climbing algorithm, instead of a best-improvement (steepest-ascent) one, for the definition and extraction of the basins of attraction of the landscape optima. A statistical analysis comparing best and first improvement network models for...

this article presents the application of two algorithms: heuristic big bang-big crunch (hbb-bc) and a heuristic particle swarm ant colony optimization (hpsaco) to discrete optimization of reinforced concrete planar frames subject to combinations of gravity and lateral loads based on aci 318-08 code. the objective function is the total cost of the frame which includes the cost of concrete, formw...

For some years now, Meta-Heuristic methods have demonstrated their ability to tackle large-scale optimisation problems. Up to now, several frameworks have been implemented for this family of methods. Some of them are either dedicated to Local Search such as EasyLocal++[5], Localizer[8], LocalSearch framework[1], Templar[7], HotFrame[4] or to Evolutionary Computation such as EOS[2], EASEA[3]. Th...

Budgeted Red-Blue Median is a generalization of classic k-Median in that there are two sets of facilities, say R and B, that can be used to serve clients located in some metric space. The goal is to open kr facilities in R and kb facilities in B for some given bounds kr, kb and connect each client to their nearest open facility in a way that minimizes the total connection cost. We extend work b...

Budgeted Red-Blue Median is a generalization of classic k-Median in that there are two sets of facilities, say R and B, that can be used to serve clients located in some metric space. The goal is to open kr facilities in R and kb facilities in B for some given bounds kr, kb and connect each client to their nearest open facility in a way that minimizes the total connection cost. We extend work b...

The article presents a local search approach for the solution of timetabling problems in general, with a particular implementation for competition track 3 of the International Timetabling Competition 2007 (ITC 2007). The heuristic search procedure is based on Threshold Accepting to overcome local optima. A stochastic neighborhood is proposed and implemented, randomly removing and reassigning ev...