TY - BOOK ID - 8286456 TI - Engineering stochastic local search algorithms : designing, implementing and analyzing effective heuristics ; second international workshop, SLS 2009, Brussels, Belgium, September 3-4, 2009 ; proceedings AU - Birattari, Mauro. AU - Hoos, Holger H. AU - Stutzle, Thomas. AU - SLS 2009 PY - 2009 SN - 364203750X 3642037518 PB - Berlin ; New York : Springer, DB - UniCat KW - Computer algorithms KW - Electronic information resource searching KW - Search theory KW - Heuristic programming KW - Stochastic programming KW - Computer Science KW - Engineering & Applied Sciences KW - Computer searching KW - Electronic searching KW - Online searching KW - Searching electronic information resources KW - Computer science. KW - Computer programming. KW - Data structures (Computer science). KW - Algorithms. KW - Computer logic. KW - Computer Science. KW - Programming Techniques. KW - Data Structures. KW - Data Structures, Cryptology and Information Theory. KW - Data Storage Representation. KW - Algorithm Analysis and Problem Complexity. KW - Logics and Meanings of Programs. KW - Computer science logic KW - Logic, Symbolic and mathematical KW - Algorism KW - Algebra KW - Arithmetic KW - Information structures (Computer science) KW - Structures, Data (Computer science) KW - Structures, Information (Computer science) KW - Electronic data processing KW - File organization (Computer science) KW - Abstract data types (Computer science) KW - Computers KW - Electronic computer programming KW - Electronic digital computers KW - Programming (Electronic computers) KW - Coding theory KW - Informatics KW - Science KW - Foundations KW - Programming KW - Linear programming KW - Operations research KW - Artificial intelligence KW - Programming (Mathematics) KW - Information retrieval KW - Data structures (Computer scienc. KW - Computer software. KW - Logic design. KW - Data Structures and Information Theory. KW - Design, Logic KW - Design of logic systems KW - Digital electronics KW - Electronic circuit design KW - Logic circuits KW - Machine theory KW - Switching theory KW - Software, Computer KW - Computer systems KW - Recursos electrònics en xarxa KW - Cerca a Internet KW - Programació estocàstica KW - Programació lineal KW - Cerca a la WEB KW - Cerca per Internet KW - Cerca web KW - Recerca a Internet KW - Recerca de la informació per Internet KW - Internet KW - Recuperació de la informació KW - Cercadors d'Internet KW - Alfabetització informacional KW - Informació electrònica KW - Recursos d'Internet KW - Recursos en Internet KW - Recursos en línia KW - Recursos Web KW - Recursos electrònics KW - Canals de continguts (RSS) KW - Catalogació de recursos electrònics en xarxa KW - Llocs web KW - Serveis electrònics de referència (Biblioteques) KW - Artificial intelligence—Data processing. KW - Information theory. KW - Information retrieval. KW - Computer architecture. KW - Data Science. KW - Computer Science Logic and Foundations of Programming. KW - Architecture, Computer KW - Data retrieval KW - Data storage KW - Discovery, Information KW - Information discovery KW - Information storage and retrieval KW - Retrieval of information KW - Documentation KW - Information science KW - Information storage and retrieval systems KW - Communication theory KW - Communication KW - Cybernetics UR - https://www.unicat.be/uniCat?func=search&query=sysid:8286456 AB - Stochastic local search (SLS) algorithms are established tools for the solution of computationally hard problems arising in computer science, business adm- istration, engineering, biology, and various other disciplines. To a large extent, their success is due to their conceptual simplicity, broad applicability and high performance for many important problems studied in academia and enco- tered in real-world applications. SLS methods include a wide spectrum of te- niques, ranging from constructive search procedures and iterative improvement algorithms to more complex SLS methods, such as ant colony optimization, evolutionary computation, iterated local search, memetic algorithms, simulated annealing, tabu search, and variable neighborhood search. Historically, the development of e?ective SLS algorithms has been guided to a large extent by experience and intuition. In recent years, it has become - creasingly evident that success with SLS algorithms depends not merely on the adoption and e?cient implementation of the most appropriate SLS technique for a given problem, but also on the mastery of a more complex algorithm - gineering process. Challenges in SLS algorithm development arise partly from the complexity of the problems being tackled and in part from the many - grees of freedom researchers and practitioners encounter when developing SLS algorithms. Crucial aspects in the SLS algorithm development comprise al- rithm design, empirical analysis techniques, problem-speci?c background, and background knowledge in several key disciplines and areas, including computer science, operations research, arti?cial intelligence, and statistics. ER -