Application of fuzzy optimization in forecasting and planning of construction industry
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KünyeVasant, P., Barsoum, N., Kahraman, C., & Dimirovski, G. M. (2008). Application of fuzzy optimization in forecasting and planning of construction industry. In D. Vrakas & I. P. Vlahavas (Eds.), Artificial Intelligence for Advanced Problem Solving Techniques (pp. 254-265). Hershey, PA: IGI Global. http://dx.doi.org/10.4018/978-1-59904-705-8.ch010
This chapter proposes a new method to obtain optimal solution using satisfactory approach in uncertain environments. The optimal solution is obtained by using possibilistic linear programming approach and intelligent computing by MATLAB®. The optimal solution for profit function, index quality, and worker satisfaction index in the construction industry is considered. Decision makers and implementers tabulate the final possibilistic and realistic outcome for objective functions with respect to level of satisfaction and vagueness for forecasting and planning. When the decision maker finds the optimum parameters with acceptable degrees of satisfaction, the decision makes can apply the confidence of gaining much profit in terms of helping the public with high quality and low cost products. The proposed fuzzy membership function allows the implementer to find a better arrangement for the equipments in the production line to fulfill the wanted products in an optimum way.