Search for lost or hidden things is a very interesting and complicated issue. This problem concentrates on the study of how to exploit resources to discover a target with unknown location. On the other hand, search problem may be formulated as a difficult decision problem because it is affected by various crucial decision factors such as search cost, search time, the probability of discovering, etc. In this paper, a new multi-criteria decision making (MCDM) approach on the basis of best-worst method (BWM) and simple additive weighting (SAW) is suggested to rank potential locations of lost or hidden targets. BWM is a novel subjective weighting technique and compared to the most common subjective method, analytic hierarchy process (AHP), requires fewer comparisons and gives more trustworthy outcomes. In this paper, BWM is used to gain the criteria weights and SAW is employed to rank the locations regarding the decision factors. This study demonstrates that BWM is easier and works better than AHP, also perfect agreement in the results of COPRAS, TOPSIS and SAW is observed. The suggested approach is very easy as well as flexible and provides an efficient method which can be developed to tackle other decision problems.

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hidden bwm copras topsis search cost search subjective weighting technique probability of discovering decision problems lost criteria weights ahp subjective method analytic hierarchy process additive weighting saw multicriteria decision making mcdm approach bestworst method

Alireza Sotoudeh-Anvari,Seyed Jafar Sadjadi,Seyed Mohammad Hadji Molana,Soheil Sadi-Nezhad,.A new MCDM-based approach using BWM and SAW for optimal search model . 7 (4),.

Alireza Sotoudeh-Anvari,Seyed Jafar Sadjadi,Seyed Mohammad Hadji Molana,Soheil Sadi-Nezhad,"A new MCDM-based approach using BWM and SAW for optimal search model " 7

Alireza Sotoudeh-Anvari,Seyed Jafar Sadjadi,Seyed Mohammad Hadji Molana,Soheil Sadi-Nezhad,"A new MCDM-based approach using BWM and SAW for optimal search model "