A storage allocation algorithm for outbound containers based on the outer–inner cellular automaton

The storage allocation problem of outbound containers in container yard is usually optimized by two successive stages, yard-bay allocation problem (YBAP) and space allocation problem (SAP), but they cannot obtain global optimal solution. This paper proposes an outer–inner cellular automaton algorith...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Information sciences Jg. 281; S. 147 - 171
Hauptverfasser: Hu, Wenbin, Wang, Huan, Min, Zhenyu
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Inc 10.10.2014
Schlagworte:
Algorithms
Allocations
Automation
Bay allocation
Branch and bound method
Cellular
Cellular automata
Computer assisted instruction
Containers
Integrated optimization
Optimization
Outer–inner cellular automaton
Space allocation
Integrated optimization
Bay allocation
Branch and bound method
Outer–inner cellular automaton
Space allocation
ISSN:0020-0255, 1872-6291
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The storage allocation problem of outbound containers in container yard is usually optimized by two successive stages, yard-bay allocation problem (YBAP) and space allocation problem (SAP), but they cannot obtain global optimal solution. This paper proposes an outer–inner cellular automaton algorithm (CAOI) to solve this problem, using YBAP and SAP as an integrated optimization process. Our work can be divided into several parts: (1) The outer cellular automaton (CAO) model is established to solve YBAP, and the inner cellular automaton (CAI) model is established to solve SAP. (2) In CAO model, an End–Front–Front–End (EFFE) transition rule is designed to make a cell change its state more instructive. (3) In CAI model, cells are initialized through a branch and bound method based on least-cost priority queue (LCBB). LCBB makes initial CAI cell space in an approximate optimal state. (4) An integrated strategy for CAO and CAI model is proposed, by which CAO and CAI execute co-evolution under the control of CAOI. Extensive experiments show CAOI achieves a better performance in solving storage allocation problem than other state-of-the-art methods, which synchronously optimizes the container transportation distance, the number of allocated yard-bays and rehandles.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0020-0255
1872-6291
DOI:10.1016/j.ins.2014.05.022