Stochastic Local Search: Foundations and Applications
Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems in many areas of computer science and operations research, including propositional satisfiability, constraint satisfaction, routing, and scheduling. SLS algorithms have also become increasingly popular for solving challenging combinatorial problems in many application areas, such as e-commerce and bioinformatics.
Hoos and Stützle offer the first systematic and unified treatment of SLS algorithms. In this groundbreaking new book, they examine the general concepts and specific instances of SLS algorithms and carefully consider their development, analysis and application. The discussion focuses on the most successful SLS methods and explores their underlying principles, properties, and features. This book gives hands-on experience with some of the most widely used search techniques, and provides readers with the necessary understanding and skills to use this powerful tool.
*Provides the first unified view of the field.
*Offers an extensive review of state-of-the-art stochastic local search algorithms and their applications.
*Presents and applies an advanced empirical methodology for analyzing the behavior of SLS algorithms.
*A companion website offers lecture slides as well as source code and Java applets for exploring and demonstrating SLS algorithms.
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algorithms for SAT applied behaviour candidate solution Chapter CNF formula colour combinatorial problems complexity constraints corresponding distribution edges efficiently empirical encoding evaluation function evaluation function value Evolutionary Algorithms example flipped Genetic Algorithms given problem instance GLSM model graph graph colouring GSAT GWSAT Hoos initialisation Las Vegas algorithms machine MAX-CSP mechanism minima neighbour neighbourhood relation NP-hard obtained optimal solution optimisation problems parameter performance perturbation pheromone plateau probabilistic random walk randomised randomly restart rithms RTDs run-time SAT instances satisfied scheduling problems search algorithms search landscape search methods search position search procedure search process search space search steps selected Simulated Annealing SLS algorithms SLS methods solution components solution quality solving state-of-the-art stochastic local search Stützle subsidiary local search tabu search techniques tion tour Travelling Salesman Problem TSP instances types typically Uninformed Random unsatisfied variant Vegas algorithms vertex vertices WalkSAT weighted MAX-SAT