Two Metaheuristics for Multiobjective Stochastic Combinatorial Optimization

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.

• Type: Conference
• Year: 2005
• Where: SAGA
• Authors: Walter J. Gutjahr
• Keywords: Ant Colony Optimization, Colony Optimization Paradigm, SAGA 2005, Stochastic Combinatorial Optimization