General local search heuristics in Combinatorial Optimization: a tutorial

Abstract

The paper presents four general heuristic search strategies that can in principle be adapted to any combinatorial optimization problem. All these techniques, Simulated Annealing (SA), Tabu Search (TS), Genetic Algorithms (GA) and Neural Networks (NN), can be described as local search heuristics. We provide an elementary description of each of them together with examples of applications and a bibliographic and historic note. More advanced developments in the framework of each strategy are outlined.