Truck dock assignment problem with time windows and capacity constraint in transshipment network through crossdocks

Authors:
Andrew Lim;Hong Ma;Zhaowei Miao
Affiliations:
Dept of Industrial Engineering and Logistics Management, Hong Kong Univ of Science and Technology, Kowloon, Hong Kong;Dept of Industrial Engineering and Logistics Management, Hong Kong Univ of Science and Technology, Kowloon, Hong Kong;Dept of Industrial Engineering and Logistics Management, Hong Kong Univ of Science and Technology, Kowloon, Hong Kong
Venue:
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part III
Year:
2006

Citing 6
Cited 3

A survey of dynamic network flows

Annals of Operations Research
An optimal solution to a dock door assignment problem

Proceedings of the 14th annual conference on Computers and industrial engineering
Tabu Search

Tabu Search
Reducing Labor Costs in an LTL Crossdocking Terminal

Operations Research
Airport Gate Scheduling with Time Windows

Artificial Intelligence Review
The over-constrained airport gate assignment problem

Computers and Operations Research

A robust two-phase heuristic algorithm for the truck scheduling problem in a resource-constrained crossdock

Computers and Operations Research
Vehicle routing scheduling using an enhanced hybrid optimization approach

Journal of Intelligent Manufacturing
Analysis of different approaches to cross-dock truck scheduling with truck arrival time uncertainty

Computers and Industrial Engineering

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we consider the over-constrained truck dock assignment problem with time windows and capacity constraint in transshipment network through crossdocks where the number of trucks exceeds the number of docks available, the capacity of the crossdock is limited, and where the objective is to minimize the total shipping distances. The problem is first formulated as an Integer Programming (IP) model, and then we propose a Tabu Search (TS) and a Genetic algorithms (GA) that utilize the IP constraints. Computational results are provided, showing that the heuristics perform better than the CPLEX Solver in both small-scale and large-scale test sets. Therefore, we conclude that the heuristic search approaches are efficient for the truck dock assignment problem. Areas: Heuristics, industrial applications of AI.