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11

SAGA
2005
Springer

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Two Metaheuristics for Multiobjective Stochastic Combinatorial Optimization

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Two Metaheuristics for Multiobjective Stochastic Combinatorial Optimization

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Two general-purpose metaheuristic algorithms for solving multiobjective stochastic combinatorial optimization problems are introduced: SP-ACO (based on the Ant Colony Optimization paradigm) which combines the previously developed algorithms S-ACO and P-ACO, and SPSA, which extends Pareto Simulated Annealing to the stochastic case. Both approaches are tested on random instances of a TSP with time windows and stochastic service times. Keywords. Ant colony optimization, combinatorial optimization, multiobjective decision analysis, simulated annealing, stochastic optimization.

Walter J. Gutjahr

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Added	28 Jun 2010
Updated	28 Jun 2010
Type	Conference
Year	2005
Where	SAGA
Authors	Walter J. Gutjahr

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