Decision Support System induced guidance for model formulation and solution

被引:18
作者
Barkhi, R
Rolland, E
Butler, J
Fan, WG
机构
[1] Virginia Polytech Inst & State Univ, RB Pamplin Coll Business, Dept Accounting & Informat Syst, Blacksburg, VA 24061 USA
[2] Univ Calif Riverside, A Gary Anderson Grad Sch Management, Riverside, CA 92521 USA
[3] Ohio State Univ, Dept Accounting & MIS, Fisher Coll Business, Columbus, OH 43210 USA
关键词
decision support systems; decision modeling;
D O I
10.1016/j.dss.2003.12.006
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
One of the critical functions of Decision Support System (DSS) is to provide system induced decision guidance for proper model formulation and solution. We show how to incorporate this type of system induced decision guidance into the design of the next generation of DSS. We suggest that a DSS should make decisions, or at least recommendations, regarding what models should be executed to solve problems most effectively and this information should be generated inductively and used deductively. This information then becomes the meta-model to induce the user to make appropriate choices. We provide an example that will illustrate how two specific problem characteristics, namely the tightness of constraints and the linearity of constraints, influence the solution quality and solution times for a specific class of test problems. We argue that a DSS should execute different formulations of the problem that lead to satisficing solutions guiding DSS users in finding the best approach to solve complex problems. (c) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码:269 / 281
页数:13
相关论文
共 46 条
[1]  
[Anonymous], 1989, GENETIC ALGORITHM SE
[2]  
Barkhi R, 2001, J MANAGE INFORM SYST, V18, P259
[3]   A new paradigm for computer-based decision support [J].
Beynon, M ;
Rasmequan, S ;
Russ, S .
DECISION SUPPORT SYSTEMS, 2002, 33 (02) :127-142
[4]   Integrating knowledge management into enterprise environments for the next generation decision support [J].
Bolloju, N ;
Khalifa, M ;
Turban, E .
DECISION SUPPORT SYSTEMS, 2002, 33 (02) :163-176
[5]   A tutorial survey of job-shop scheduling problems using genetic algorithms, part II: hybrid genetic search strategies [J].
Cheng, RW ;
Gen, M ;
Tsujimura, Y .
COMPUTERS & INDUSTRIAL ENGINEERING, 1999, 36 (02) :343-364
[6]   Sequencing parallel machining operations by genetic algorithms [J].
Chiu, NC ;
Fang, SC ;
Lee, YS .
COMPUTERS & INDUSTRIAL ENGINEERING, 1999, 36 (02) :259-280
[7]   INDUCED SYSTEM RESTRICTIVENESS - AN EXPERIMENTAL DEMONSTRATION [J].
CHU, PC ;
ELAM, JJ .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1990, 20 (01) :195-201
[8]   LOCATION OF BANK ACCOUNTS TO OPTIMIZE FLOAT - ANALYTIC STUDY OF EXACT AND APPROXIMATE ALGORITHMS [J].
CORNUEJOLS, G ;
FISHER, ML ;
NEMHAUSER, GL .
MANAGEMENT SCIENCE, 1977, 23 (08) :789-810
[9]   A PRIMAL APPROACH TO THE SIMPLE PLANT LOCATION PROBLEM [J].
CORNUEJOLS, G ;
THIZY, JM .
SIAM JOURNAL ON ALGEBRAIC AND DISCRETE METHODS, 1982, 3 (04) :504-510
[10]  
DENSHAM PJ, 1992, J RSAI, V71, P307