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Although after an earthquake, the injured person should be equipped with food, shelter, and hygiene activities, before anything must be searched and rescued. However, Disaster Management (DM) has focused heavily on emergency logistics and developing an e ective strategy for search operations has been largely ignored. In this study, we suggest a stochastic multi-objective optimization model to allocate resource and time for searching the individuals who are trapped in disaster regions. Since in disaster conditions, the majority of information is uncertain, our model assumes ambiguity for the locations where the missing people may exist. Fortunately, the suggested model ts nicely into the structure of the classical optimal search model as it uses a stochastic dynamic programming approach to solving this problem. On the other hand, through a computational experiment, we observed that the model needed heavy computation. Therefore, we reformulated the suggested search model for a Multi-Criteria Decision Making (MCDM) problem and employed two e cient MCDM techniques, namely TOPSIS and COPRAS, to tackle the ranking problem. Consequently, the computational e ort signi cantly decreased and a promising solution was achieved.

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. .

Purpose Delivery management of perishable products such as blood in a supply chain is a considerable issue such that the last-mile delivery, which refers to deliver goods to the end user as fast as possible takes into account as one of the most important, expensive and, polluting segments in the entire supply chain. Regardless of economic challenges, the last-mile delivery faces social and environmental barriers to continuing operations while complying with environmental and social standards, therefore incorporating sustainability into last-mile logistic strategy is no longer an option but rather a necessity. Accordingly, the purpose of this paper is to consider a last-mile delivery in a blood supply chain in terms of using appropriate technologies such as drones to assess sustainability. Design/methodology/approach The authors discuss the impact of drone technology on last-mile delivery and its importance in achieving sustainability. They focus on the effect of using drones on CO2 emission, costs and social benefits by proposing a multi-objective mathematical model to assess sustainability in the last-mile delivery. A preemptive fuzzy goal programming approach to solve the model and measure the achievement degree of sustainability is conducted by using a numerical example to show the capability and usefulness of the suggested model, solution approach and, impact of drone technology in achieving all three aspects of sustainability. Findings The findings illustrate the achievement degree of sustainability in the delivery of blood based on locating distribution centers and allocating drones. Moreover, a comparison between drones and conventional vehicles is carried out to show the preference of using drones in reaching sustainability. A sensitivity analysis on aspects of sustainability and specifications of drone technology is conducted for validating the obtained results and distinguishing the most dominant aspect and parameters in enhancing the achievement degree of sustainability. Originality/value To the best of the authors’ knowledge, no research has considered the assessment of sustainability in the last-mile delivery of blood supply chain with a focus on drone technology.