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An algorithm for systems welfare interactive goal programming modelling
Institution:1. School of Kinesiology, Auburn University, 301 Wire Road, AL 36849, USA;2. CAPES Foundation, Ministry of Education of Brazil, Brasilia, DF 70040-020, Brazil;3. Department of Health, Kinesiology, and Recreation, University of Utah, USA;4. Department of Physical Therapy and Athletic Training, University of Utah, USA;1. Department of Nursing I, University School of Nursing, University of the Basque Country, Leioa, Bizkaia, Spain;2. Department of Physiology, Faculty of Medicine and Dentistry, University of the Basque Country, Leioa, Bizkaia, Spain;3. “Matia Instituto Gerontológico” Foundation, Donostia, Gipuzkoa, Spain
Abstract:Every human system is faced with the problem of choosing between alternative options, and methods of interactive programming have been suggested as the best way to lead decision makers reach decisions that are consistent with their preferences. However, even though a large number of interactive algorithms have been proposed for multiobjective decision making (MODM), there is yet no truly interactive goal programming (GP) algorithm, despite the preference of GP over other MODM methodologies. The current paper presents an algorithm for interactive GP modelling called SWIGP (systems welfare interactive GP) which ensures that the overall welfare of the system under consideration is adequately taken into account in the interactive process. To achieve this, this paper distinguishes between technical, allocative and economic efficiencies and combines an economic efficiency index with interactive GP process. Besides being of wide applicability, the algorithm exerts little cognitive burden on the decision maker (DM). Indeed, even if the DM is assumed to operate under conditions of complete ignorance, SWIGP provides the direction for searching the “best” compromise solution. Moreover, the algorithm converges very fast because of the economic efficiency index that complements the interactive process in aiding the DM arrive at a most preferred solution.
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