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N. Kasabov (1996)
Foundations Of Neural Networks, Fuzzy Systems, And Knowledge Engineering [Books in Brief]IEEE Transactions on Neural Networks, 8
N.K. Kasabov
Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering
Ke Wan, R. Levary (1995)
A LINEAR-PROGRAMMING-BASED PRICE NEGOTIATION PROCEDURE FOR CONTRACTING SHIPPING COMPANIESTransportation Research Part A-policy and Practice, 29
S. Mason, P. Ribera, J. Farris, Randall Kirk (2003)
INTEGRATING THE WAREHOUSING AND TRANSPORTATION FUNCTIONS OF THE SUPPLY CHAINTransportation Research Part E-logistics and Transportation Review, 39
W. Shen, C. Khoong (1995)
A DSS for empty container distribution planningDecis. Support Syst., 15
R. Sharda (1994)
Neural Networks for the MS/OR Analyst: An Application BibliographyInterfaces, 24
P. Wasserman (1989)
Neural computing: theory and practice
B. Devlin, L. Cote (1996)
Data Warehouse: From Architecture to Implementation
S. Haykin (1998)
Neural Networks: A Comprehensive Foundation
M. Porter, Victor Millar (1985)
How Information Gives You Competitive Advantage
M. Stopford (2002)
E-COMMERCE-IMPLICATIONS, OPPORTUNITIES AND THREATS FOR THE SHIPPING BUSINESSInternational Journal of Transport Management, 1
T.H. Davenport, L. Prusak
Working Knowledge
W.H. Inmon
Data warehouse – a perspective of data over time
Anindya Datta, Helen Thomas (1999)
The cube data model: a conceptual model and algebra for on-line analytical processing in data warehousesDecis. Support Syst., 27
The emergence of advanced information technologies strengthens the capability to the entrepreneur to manage and manipulate data. However, the quality of information, the capability of providing the right information to the right person, and the utilization of information are still in doubt. Therefore, increasing numbers of firms have realized and started to develop as well as improve their existing information systems to fit the ever‐changing business needs of the organization to support decision‐making for the volatile business environment. Indeed, previous research studies have found that logistics management is the great frontier of cost reduction. Therefore, in this paper, an infrastructure of a decision support system is proposed to capture and maintain the business and resources allocation information with the adoption of the neural network for its artificial intelligent characteristic that mimic the operation of human brain to generate solutions systematically. The proposed system is adopted by a shipping company to assist allocation of containers.
Journal of Manufacturing Technology Management – Emerald Publishing
Published: Dec 1, 2004
Keywords: Decision support systems; Resource allocation; Neural nets; Artificial intelligence
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