WSC '95 Proceedings of the 27th conference on Winter simulation
Using a simulation model to evaluate the configuration of a sortation facility
Proceedings of the 29th conference on Winter simulation
Practical genetic algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
The parcel hub scheduling problem: a simulation-based solution approach
Computers and Industrial Engineering
Genetic-based scheduling to solve the parcel hub scheduling problem
Computers and Industrial Engineering
A dynamic load-balancing scheme for the parcel hub-scheduling problem
Computers and Industrial Engineering
Iterative improvement to solve the parcel hub scheduling problem
Computers and Industrial Engineering
A beam search heuristics to solve the parcel hub scheduling problem
Computers and Industrial Engineering
Computers and Industrial Engineering
A tabu search approach to the truck scheduling problem with multiple docks and time windows
Computers and Industrial Engineering
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This paper addresses the scheduling of inbound trailers to unload docks at central parcel consolidation terminals in the parcel delivery industry, an industry that operates in a time-critical environment. The scheduling function can have a significant impact on the amount of time required to unload the inbound trailers and sort and load the parcels to the outbound trailers. This problem is known as the parcel hub scheduling problem (PHSP). To solve the PHSP, a simulation-based scheduling approach with an embedded genetic algorithm is proposed. The results show that the proposed scheduling approach is able to reduce the amount of time required to unload the inbound trailers by approximately 3.5 percent compared to a previously developed algorithm and about 16.1 percent compared to an approach that is representative of current industry practice.