Genetic algorithms for door-assigning and sequencing of trucks at distribution centers for the improvement of operational performance

Authors:
Kangbae Lee;Byung Soo Kim;Cheol Min Joo
Affiliations:
Department of Management Information Systems, Dong-A University, Busan 602-760, Republic of Korea;Graduate School of Management of Technology, Pukyong National University, Busan 608-737, Republic of Korea;Department of Industrial and Management Engineering, Dongseo University, Busan 617-716, Republic of Korea
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

In a supply chain, cross docking is one of the most innovative systems for improving the operational performance at distribution centers. By utilizing this cross docking system, products are delivered to the distribution center via inbound trucks and immediately sorted out. Then, products are shipped to customers via outbound trucks and thus, no inventory remains at the distribution center. In this paper, we consider the scheduling problem of inbound and outbound trucks at distribution centers. The aim is to maximize the number of products that are able to ship within a given working horizon at these centers. In this paper, a mathematical model for an optimal solution is derived and intelligent genetic algorithms are proposed. The performances of the genetic algorithms are evaluated using several randomly generated examples.