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Unformatted text preview: Applied Mathematics Systematic Diversification Metaheuristic for the Vehicle Routing Problem with Time Windows OLLI BRÄYSY, GEIR HASLE SINTEF Applied Mathematics, Department of Optimisation, P.O. Box 124 Blindern, N0314 Oslo, Norway {Olli.Braysy;Geir.Hasle}@sintef.no JEAN BERGER and MOHAMED BARKAOUI Defence Research Establishment Valcartier, Decision Support Technology Section 2459 PieXI Blvd. North, ValBélair, PQ, Canada, G3J 1X5 email: [email protected], [email protected] Applied Mathematics Introduction Development of a new metaheuristic, Systematic Diversification for combinatorial optimization problems Applied to threephase multistart local search framework of Bräysy et al. (2002) for Vehicle Routing Problem with Time Windows (VRPTW) Coupled with a Threshold Accepting postoptimization procedure Computational results reported for the wellknown 100customer benchmarks of Solomon (1987). The findings indicate that the results are within 0.3% from the best known on the average. IFORS 2002, Edinburgh, Scotland, July 812 Applied Mathematics Generation of the LS solution Reduce the number of routes Reduce distance Injection trees Modified CROSS exchanges Build initial solutions Hybrid construction heuristic IFORS 2002, Edinburgh, Scotland, July 812 PROCESS METHOD Applied Mathematics Systematic Diversification The basic idea is to maximize differences between individuals in a population based search method Based on common attribute (arcs) Intensification using the local search Changes that increase the number of common attributes with respect to previously obtained individuals penalized or blocked Applied to multistart framework Penalizes selection of common attributes or identifies the set of most diverse individuals Limit to worsening of the objective function value Used to guide the creation of initial solutions and distance improvement heuristics Applied Mathematics Hybrid sequential insertion heuristic Initialization: seed customer randomly selected among the farthest from the depot or among the ones having the earliest deadline Insert the cheapest customer in the best feasible insertion place Weighted cost function of additional detour and waiting time Subtract the distance of the customer to the depot...
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 Winter '08
 JARVIS
 Applied Mathematics, Optimization, Scotland, Edinburgh, local search, Threshold Accepting, Systematic Diversification

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