Operations Research
Ant algorithms for discrete optimization
Artificial Life
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A hybrid scatter search for the probabilistic traveling salesman problem
Computers and Operations Research
MDAI '07 Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence
Routing optimization heuristics algorithms for urban solid waste transportation management
WSEAS Transactions on Computers
A survey on metaheuristics for stochastic combinatorial optimization
Natural Computing: an international journal
Computers and Operations Research
A hybrid honey bees mating optimization algorithm for the probabilistic traveling salesman problem
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Structure Design of the 3-D Braided Composite Based on a Hybrid Optimization Algorithm
AICI '09 Proceedings of the International Conference on Artificial Intelligence and Computational Intelligence
A priori parallel machines scheduling
Computers and Industrial Engineering
New ideas for applying ant colony optimization to the probabilistic TSP
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
Estimation-based metaheuristics for the probabilistic traveling salesman problem
Computers and Operations Research
Research on coaxiality errors evaluation based on ant colony optimization algorithm
LSMS'07 Proceedings of the Life system modeling and simulation 2007 international conference on Bio-Inspired computational intelligence and applications
Near-optimal joint selection of transmit and receive antennas for MIMO systems
ISCIT'09 Proceedings of the 9th international conference on Communications and information technologies
A new evolutionary algorithm using shadow price guided operators
Applied Soft Computing
Analysis of various swarm-based & ant-based algorithms
ACAI '11 Proceedings of the International Conference on Advances in Computing and Artificial Intelligence
Bridging the syntactic and the semantic web search
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Initial application of ant colony optimisation to statistical disclosure control
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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The Probabilistic Traveling Salesman Problem (PTSP) is a TSP problem where each customer has a given probability of requiring a visit. The goal is to find an a priori tour of minimal expected length over all customers, with the strategy of visiting a random subset of customers in the same order as they appear in the a priori tour.We address the question of whether and in which context an a priori tour found by a TSP heuristic can also be a good solution for the PTSP. We answer this question by testing the relative performance of two ant colony optimization algorithms, Ant Colony System (ACS) introduced by Dorigo and Gambardella for the TSP, and a variant of it (pACS) which aims to minimize the PTSP objective function.We show in which probability configuration of customers pACS and ACS are promising algorithms for the PTSP.