A Decision Generator Shell in Prolog
Many decision problems can be considered as searching for an element in a finite set. Classical approaches lead to sophisticated combinatorial optimization algorithms that exploit a lot of the structure of the decision situation. Often these algorithms are not easy to adapt to new constraints on decisions imposed by the decision makers.
Our approach to the generation of decisions is to use general search methods that are easy to adapt in case of new constraints. In general they give less good decisions but are more robust. A general-purpose shell based on these search methods is sketched using Prolog. As an illustration two decision problems are treated: the travelling salesman problem and precedence constrained scheduling.
KeywordsCompletion Time Decision Support System Search Method Domain Knowledge Travelling Salesman Problem
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- Aarts, E.H.L. and Korst, J., Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing, Wiley, 1989.Google Scholar
- Checkland, P., Systems Thinking and Systems Practice, Wiley, 1981.Google Scholar
- Eiben, A.E. and van Hee, K.M.: Knowledge Representation and Search Methods for Decision Support Systems, in: Gaul, W. and Schader, M., Ed., Data, Expert Knowledge and Decisions, Springer -Verlag, 1990.Google Scholar
- Garey, M.R. and Johnson, D.S., Computers and Intractability: A Guide to the Theory of NP-completeness, Freeman and Co, 1978.Google Scholar
- van Hee, K.M. and Lapinski, A., OR and AI approaches to decision support, Decision Support Systems 4 (1989), pp 447–459.Google Scholar
- Keen, P.G.W. and Scott Morton, M.S., Decision support systems: an organized perspective, Addison-Wesley, 1978.Google Scholar
- Papadimitriou, C.H. and Stieglitz, K., Combinatorial optimization: algorithms and complexity, Prentice -Hall, 1982.Google Scholar
- Pearl, J.R., Artificial intelligence: the heuristic programming approach, McGraw-Hill, 1971.Google Scholar
- Schnupp, P. and Bernhard L.W., Productive Prolog Programming, Prentice Hall, 1986.Google Scholar
- Spivey, M., The Z notation, Prentice Hall, 1989.Google Scholar