A Monte Carlo investigation of incomplete pairwise comparison matrices in AHP

Article Abstract:

A Monte Carlo simulation method was used to assess the feasibility of modifying the Analytic Hierarchy Process (AHP) that would lead to lesser collection of data. The method employed the Incomplete Pairwise Comparisons (IPC) algorithm to analyze the impact of lessened sets of pairwise comparisons in the AHP. The process revealed that attribute level weights can be attained through the use of incomplete sets of pairwise comparison matrices without aggravating the preciseness and independence of decision model.

Research and Development in the Physical, Engineering, and Life Sciences, Mathematics, Decision-making, Models, Decision making

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Modelling stochastic decision systems using dependent-chance programming

Article Abstract:

Monte Carlo simulation based genetic algorithm may be used to solve complex models of stochastic decision systems formulated through dependent-chance programming. Steps in modelling include defining the stochastic decision environment by stochastic sets, analyzing the relationships if there are multiple events, assigning sets to events and assigning criteria to events using chance functions.

Management Theory & Techniques, Operations Research, Management, Stochastic programming

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