Scatter Search: Basic Design and Advanced Strategies

Scatter search is an evolutionary method that has been successfully applied to hard optimization problems. The fundamental concepts and principles of the method were first proposed in the 1970s and were based on formulations, dating back to the 1960s, for combining decision rules and problem constraints. The combination strategy was devised with the belief that information could be exploited more effectively when integrated than when treated in isolation. In contrast to other evolutionary methods like genetic algorithms, scatter search is mostly based on systematic designs and methods with the purpose of creating new solutions. It uses strategies for search diversification and intensification that have proved effective in a variety of optimization problems. The Scatter Search framework is flexible, allowing the development of alternative implementations with varying degrees of sophistication. This paper's goal is to provide a grounding in the essential ideas of Scatter Search that will enable readers to create successful applications of their own. The paper also introduces an application of the method to solve the well-known knapsack problem, in order to illustrate some implementation details.