A complete and an incomplete algorithm for automated guided vehicle scheduling in container terminals

Authors:
Hassan Rashidi;Edward P. K. Tsang
Affiliations:
Department of Statistics, Mathematics, and Computer Science, Allameh Tabataba'i University, No. 4, Ahmad Ghasir St., Shahid Beheshti st., Tehran, Iran;School of Computer Science and Electronic System Engineering, University of Essex, Colchester CO4 3SQ, UK
Venue:
Computers & Mathematics with Applications
Year:
2011

Citing 6
Cited 0

An efficient implementation of a scaling minimum-cost flow algorithm

Journal of Algorithms
Clustering for faster network simplex pivots

SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
Pivot Strategies for Primal-Simplex Network Codes

Journal of the ACM (JACM)
Algorithms for the Simple Equal Flow Problem

Management Science
A decision support system for operations in a container terminal

Decision Support Systems
A network simplex algorithm with O(n) consecutive degenerate pivots

Operations Research Letters

Quantified Score

Hi-index	0.09

Visualization

Abstract

In this paper, a scheduling problem for automated guided vehicles in container terminals is defined and formulated as a Minimum Cost Flow model. This problem is then solved by a novel algorithm, NSA+, which extended the standard Network Simplex Algorithm (NSA). Like NSA, NSA+ is a complete algorithm, which means that it guarantees optimality of the solution if it finds one within the time available. To complement NSA+, an incomplete algorithm Greedy Vehicle Search (GVS) is designed and implemented. The NSA+ and GVS are compared and contrasted to evaluate their relative strength and weakness. With polynomial time complexity, NSA+ can be used to solve very large problems, as verified in our experiments. Should the problem be too large for NSA+, or the time available for computation is too short (as it would be in dynamic scheduling), GVS complements NSA+.