The break-bulk role of terminals in many-to-many logistic networks
Operations Research
Scheduling two parallel semiautomatic machines to minimize machine interference
Computers and Operations Research
Using a simulation model to evaluate the configuration of a sortation facility
Proceedings of the 29th conference on Winter simulation
The harpy speech recognition system.
The harpy speech recognition system.
The argos image understanding system.
The argos image understanding system.
Constraint-directed search: a case study of job-shop scheduling
Constraint-directed search: a case study of job-shop scheduling
A dock-door assignment problem for the Korean mail distribution center
Computers and Industrial Engineering - Special issue: Logistics and supply chain management
Computers and Industrial Engineering
The parcel hub scheduling problem: A simulation-based solution approach
Computers and Industrial Engineering
Depth-first vs. best-first search: new results
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
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In this paper, a beam search scheduling heuristic (BSSH) is presented to solve the parcel hub scheduling problem (PHSP), which is a scheduling problem that is common in the parcel delivery industry (PDI). Companies in the PDI include the United States Postal Service, United Parcel Services, Federal Express, and Deutsche Post. Together, these companies move more than one trillion dollars of the United States' Gross Domestic Product. The PHSP involves scheduling a set of inbound trailers each containing a set of heterogeneous parcels to a set of unload docks. At the unload docks, the parcels are unloaded, sorted, and moved to the appropriate outbound trailers at the load docks. At the load docks, the parcels are loaded onto the outbound trailers. The objective is to minimize the timespan of the transfer operation at the transshipment terminal. The BSSH is compared to various scheduling approaches: random scheduling algorithm (RSA), genetic-based scheduling algorithm (GBSA), and simulation-based scheduling algorithm (SBSA). While GBSA and SBSA offer solutions that are superior to BSSH for smaller size problems, BSSH outperforms these algorithms on larger size problems requiring much less computational time. The results show that for larger size problems the BSSH is able to produce solutions that are from 4% to 8% of the known optimum solutions. In contrast, GBSA and SBSA, respectively offer solutions from 23% to 38% and from 6% to 47% of the known optimum solutions. The contribution of this paper is a scheduling heuristic to solve the PHSP.