Real Life Decision Optimization Model

Abstract

Abstract: In real life scientific and engineering problems decision making is common practice. Decision making include single decision maker or group of decision makers. Decision maker’s expressions consists imprecise, inconsistent and indeterminate information. Also, the decision maker cannot select the best solution in unidirectional (single goal) way. Therefore, proposed model adopts decision makers’ opinions in Neutrosophic Values (SVNS/INV) which effectively deals imprecise, inconsistent and indeterminate information, Multi goal (criteria) decision making and creditability (due to partial knowledge of decision maker) associated decision makers’ expressions. Then partially known or unknown priorities (weights) of Multi Criteria Group Decision Making (MCGDM) problem is determined by establishing Correlation Coefficient (CC) established from improved cross entropy linear programming technique. The Multi Goal Linear equation was solved using a Novel Self Adaptive Harmonic Search Algorithm. The (NSAH) alternate solutions were ranked by weighted correlation coefficients of each alternative (lower the CC higher will be the rank). The validation of proposed method was demonstrated with an illustrative examples and compare with recent advancements. Hence, the proposed method was effective, flexible and accurate.