A new heuristic for the period traveling salesman problem
Computers and Operations Research
An asynchronous parallel metaheuristic for the period vehicle routing problem
Future Generation Computer Systems - Special issue on bio-impaired solutions to parallel processing problems
The period traveling salesman problem: a new heuristic algorithm
Computers and Operations Research
A Savings Based Ant System For The Vehicle Routing Problem
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
A Branch-and-Cut Procedure for the Vehicle Routing Problem with Time Windows
Transportation Science
A Reactive Variable Neighborhood Search for the Vehicle-Routing Problem with Time Windows
INFORMS Journal on Computing
D-Ants: savings based ants divide and conquer the vehicle routing problem
Computers and Operations Research
An improved heuristic for the period traveling salesman problem
Computers and Operations Research
A Two-Stage Hybrid Local Search for the Vehicle Routing Problem with Time Windows
Transportation Science
Vehicle Routing Problem with Time Windows, Part II: Metaheuristics
Transportation Science
Proceedings of the 40th Conference on Winter Simulation
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In this paper a model and several solution procedures for a novel type of vehicle routing problems where time windows for the pickup of perishable goods depend on the dispatching policy used in the solution process are presented. This problem is referred to as Vehicle Routing Problem with multiple interdependent time windows (VRPmiTW) and is motivated by a project carried out with the Austrian Red Cross blood program to assist their logistics department. Several variants of a heuristic constructive procedure as well as a branch-and-bound based algorithm for this problem were developed and implemented. Besides finding the expected reduction in costs when compared with the current procedures of the Austrian Red Cross, the results show that the heuristic algorithms find solutions reasonably close to the optimum in fractions of a second. Another important finding is that increasing the number of pickups at selected customers beyond the theoretical minimum number of pickups yields significantly greater potential for cost reductions.