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Local Search in Combinatorial Optimization
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This paper addresses the problems of selection and scheduling related to a virtual organisation in which a central service broker communicates with groups of service providers offering services of different types. Our objective is to show that these problems can be formulated in a precise manner and that well-established algorithms can be developed for solving them. Especially, Tabu Search and Simulated Annealing with Variable Neighbourhood search are proposed as options for finding near-optimal solutions to the selection and scheduling problems. In our computational experiments, the algorithms were first validated with the help of benchmark job-shop problems and then applied to a specific cutting stock problem with randomly generated instances.