The life of many people across the world can face various dangers with incurrence of incidents and unpredictable diseases. Incidents often require quick relief as they directly affect human lives. The process of planning, management and monitoring the flow of relief sources to injured and sick individuals is called relief logistics. When best relief services are provided through available sources, relief logistics appear. In this article, a multi-objective model for relief resources distribution facilities under an uncertain condition is investigated in two ways of demand satisfaction by considering the relief resources accessibility and demand satisfaction in a fuzzy logic. In the presented model, the concepts of cost, chance of demand satisfaction, elevation of response capability of system, discount levels for relief commodities, late satisfaction of demand, hub for accumulation of late and returned orders and special route for time significance in distribution of relief commodities are considered. For the first problem, the chance of relief resources accessibility and for the second problem, demands were investigated using fuzzy logic. Considering the conducted analysis, the demand amount is taken more in the second problem than the first one, which has led to an increase in the cost of the second problem. On one hand, the chance of demand satisfaction with no late orders is higher than the second problem. Satisfaction of demand occurs more in the second problem as well. Thus, these problems should be utilized in a way that suits the space of this problem. To solve the problem and to do the sensitivity analysis, we present a NSGA-II algorithm to deal with multi-objectiveness of the problem. A ε-Constraint method is also proposed to evaluate the performance of the proposed algorithm.Growing Science Ltd. All rights reserved. 7
Satisfying customer demand is one of the growing concerns of supply chain managers. On the other hand, the development of internet communications has increased online demand. In addition, the COVID-19 pandemic has increased the demand for online shopping. One of the useful concepts that help to address this concern is the omni-channel strategy, which integrates online and traditional channels with the aim of improving customer service level. For this purpose, this paper proposes an algorithm for evaluating Omni-channel Distribution Network Configurations (OCDNCs). The algorithm applies an extended Data Envelopment Analysis (DEA) model to evaluate OCDNCs based on cost, service, transparency, and environmental criteria; and then, forms a consensus on the evaluation results generated according to different criteria by utilizing an uncertain optimization model. To the best of our knowledge, this is the first attempt in which such an algorithm has been employed to take into account the mentioned criteria in a model to evaluate OCDNCs. The application of the proposed models was investigated in a case study in relation to the Indian retail industry. The results show that the configuration with the most connections among its members was the most stable, robust, and efficient.
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