The precedence-constrained asymmetric traveling salesman polytope
Mathematical Programming: Series A and B
Computers and Operations Research - Neural networks in business
A Branch & Cut Algorithm for the Asymmetric Traveling Salesman Problem with Precedence Constraints
Computational Optimization and Applications
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Tabu Search
Rollout Algorithms for Combinatorial Optimization
Journal of Heuristics
Rollout Algorithms for Stochastic Scheduling Problems
Journal of Heuristics
An Ant Colony System Hybridized with a New Local Search for the Sequential Ordering Problem
INFORMS Journal on Computing
Exact and heuristic dynamic programming algorithms for the vehicle routing problem with stochastic demands
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A heuristic manipulation technique for the sequential ordering problem
Computers and Operations Research
A hybrid particle swarm optimization approach for the sequential ordering problem
Computers and Operations Research
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In this paper we deal with the solution of the sequential ordering problem (SOP) in parallel environments. In particular, we present a parallel version of the rollout algorithm, an innovative heuristic method for solving NP-Hard combinatorial optimization problems, recently proposed by Bertsekas et al. [J. Heuristics 3 (1997) 245]. The proposed parallel algorithm has been designed by considering a cooperative multi-thread parallelization strategy, where several threads visit different portions of the solution space independently and periodically exchange information about the solutions found during the search. Such an approach allows not only to speed up the convergence to the best solution, but to find also better solutions, taking roughly the same computation time. The performance of the proposed parallel RH has been evaluated on a cluster of PCs, by considering a set of test problems taken from the TSPLIB [Orsa J. Comput. 3 (1991) 376].