Due to the importance of relief operations in disasters, this paper aims to contribute humanitarian logistics under uncertainty. In this paper, a three-level relief chain model consisting of suppliers, relief distribution centers, and affected areas is considered. The uncertainty associated with demand, supply, and all of the cost parameters is addressed by employing robust optimization, where the uncertain parameters are independent and bounded random variables. While the proposed model attempts to minimize the total costs of the relief chain, it implicitly maximizes people's satisfaction level in the affected areas through applying a penalty to shortages of relief commodities. Additionally, a data set derived from a real disaster case study in the Alborz area, which is vulnerable to earthquakes, is applied to test the efficiency of the proposed robust relief chain model compared to its deterministic form. The study analyzes the degree to which each uncertain parameter affects the solution of the relief chain model and consequently helps the decision maker to tune the parameter values more accurately.

This paper presents a robust optimization model for the design of a supply chain facing uncertainty in demand, supply capacity and major cost data including transportation and shortage cost parameters. We first present a base model that aims to determine the strategic 'location' and tactical 'allocation' decisions for a deterministic four-tier supply chain. The model is then extended to incorporate uncertainty in key input parameters using a robust optimization approach that can overcome the limitations of scenario-based solution methods in a tractable way, i.e. without excessive changes in complexity of the underlying base deterministic model. The application of the approach is investigated in an actual case study where real data is utilized to design a bread supply chain network. Numerical results obtained from model implementation and sensitivity analysis experiments arrive at important managerial insights and practical implications.

As moving businesses from face-to-face trading, mail order and telephone order to electronic commerce over open networks such as the Internet, there be an exponentially growth in electronic payment transactions. Therefore, monitoring and evaluating the current electronic payment systems greatly affects the efficiency of money transactions, trades and, finally, the overall economy of the countries. In this paper, the Iranian e-payment systems are examined as a special case. The aim is to examine and evaluate the current epayment systems, and rank they based on the experts opinions. Considering the nature of the gathered data, the analytic hierarchy process (AHP), as a decision-making method, is used to evaluate the data. The findings of this research are intended to be useful for both academic researchers and companies planning to adopt or to improve an electronic payment system.

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