TY - JOUR
T1 - The integration of expert knowledge in decision support systems for facility location planning
AU - Arentze, T.A.
AU - Borgers, A.W.J.
AU - Timmermans, H.J.P.
PY - 1995
Y1 - 1995
N2 - The integration of expert systems in DSS has led to a new generation of systems commonly referred to as knowledge-based or intelligent DSS. This paper investigates the use of expert system technology for the development of a knowledge-based DSS for the planning of retail and service facilities. The forms of knowledge involved in planning tasks are identified and organized in four layers. The layers describe the states and events in the facility system (the domain layer), their interrelationships (the inferential layer), procedures for solving well-defined subproblems (the task layer) and strategies for approaching the overall problem (the strategic layer). The potentials of decision tables for representing qualitative and complex knowledge is discussed and illustrated with applications in the field of retail planning. It is shown that expert knowledge from each of the four layers can be used to improve the modelling capabilities and intelligence of a DSS. The result is a powerful and flexible DSS that supports planning at the domain, inferential, task and strategic level dependent on the preference of the decision maker and characteristics of the problem.
AB - The integration of expert systems in DSS has led to a new generation of systems commonly referred to as knowledge-based or intelligent DSS. This paper investigates the use of expert system technology for the development of a knowledge-based DSS for the planning of retail and service facilities. The forms of knowledge involved in planning tasks are identified and organized in four layers. The layers describe the states and events in the facility system (the domain layer), their interrelationships (the inferential layer), procedures for solving well-defined subproblems (the task layer) and strategies for approaching the overall problem (the strategic layer). The potentials of decision tables for representing qualitative and complex knowledge is discussed and illustrated with applications in the field of retail planning. It is shown that expert knowledge from each of the four layers can be used to improve the modelling capabilities and intelligence of a DSS. The result is a powerful and flexible DSS that supports planning at the domain, inferential, task and strategic level dependent on the preference of the decision maker and characteristics of the problem.
U2 - 10.1016/0198-9715(95)00026-7
DO - 10.1016/0198-9715(95)00026-7
M3 - Article
SN - 0198-9715
VL - 19
SP - 227
EP - 247
JO - Computers, Environment and Urban Systems
JF - Computers, Environment and Urban Systems
IS - 4
ER -