Constraint-Based Local Search

Introducing a method for solving combinatorial optimisation problems that combines the techniques of constraint programming and local search. The ubiquity of combinatorial optimisation problems in our society is illustrated by the novel application areas for optimisation technology, which range from supply chain management to sports tournament scheduling. Over the last two decades, constraint programming has emerged as a fundamental methodology to solve a variety of combinatorial problems, and rich constraint programming languages have been developed for expressing and combining constraints and specifying search procedures at a high level of abstraction.

Local search approaches to combinatorial optimisation are able to isolate optimal or near-optimal solutions within reasonable time constraints. This book introduces a method for solving combinatorial optimisation problems that combines constraint programming and local search, using constraints to describe and control local search, and a programming language, COMET, that supports both modelling and search abstractions in the spirit of constraint programming. After an overview of local search including neighbourhoods, heuristics, and metaheuristics, the book presents the architecture and modelling and search components of constraint-based local search and describes how constraint-based local search is supported in COMET.

The book describes a variety of applications, arranged by meta-heuristics. It presents scheduling applications, along with the background necessary to understand these challenging problems. The book also includes a number of satisfiability problems, illustrating the ability of constraint-based local search approaches to cope with both satisfiability and optimisation problems in a uniform fashion.