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Aim: The objective of this paper is to design nutrient-adequate, varied and cost-efficient diets for diabetes patients.
Methods: A new multi-objective mixed integer linear programming model under uncertainty is developed to design diet plans for diabetes patients.
Findings: The analysis is conducted on the population of 30 years old men and women in 24.99 and 18.5 body mass index, 1.50, 1.65 and 1.80 (m) height categorized in 4 physical activity levels (sedentary, low, active and very active). The objectives of the model are the minimization of the total amount of saturated fat, sugar and cholesterol and the total cost of the diet plans. The constraints of the model are fulfilling the body's nutrient requirements and the diversity control of each patient’s diet. In order to get closer to the real world, fuzzy parameters are considered in the model. To solve the model, a new hybrid solution methodology (Jimenez and epsilon-constraint method) is used to offer the optimal Pareto of non-dominated solutions. Each optimal Pareto of the model consists of diet plans that each patient can choose the proper food based on the taste, availability and cost.
Conclusion: Mathematical modeling of diet planning and study of its optimal solutions can be considered as a decision support tool for the professionals to design the most proper diet plans.

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The project excellence model (PEM) evaluates projects by a comprehensive approach and measures the success and excellence of a project based on a set of pre-defined criteria. This model includes nine evaluation criteria that one of them is the “leadership” criterion. The execution responsibility of leadership in projects is undertaken by project managers. In this paper, a comprehensive conceptual competency model is presented by focusing on the PEM's leadership criterion. This model suggests three general dimensions as necessary criteria for evaluating project managers, which are knowledge competency, performance competency and behavioral competency. Moreover, in this research, to achieve optimum evaluation process, a new multi-attribute decision making (MADM) method is designed integrating the Delphi and VIKOR techniques in a fuzzy environment. The proposed competency model and fuzzy hybrid evaluation method can be considered as a decision support system (DSS) that not only helps development of the project excellence level but is a move towards systematic planning and scientific decision making in the successful project management process.

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Nowadays, reverse logistics is one of the major activities of supply chain management that are included all of physical activities related to returned products (e.g., collection, recovery and recycle). So that, designing and implementing of appropriate reverse logistics, not only lead to increase customer loyalty, but also it will be reduce the inventory and transportation costs. This paper presents a mixed-integer linear programming (MILP) model for the network design of forward and reverse logistics, which minimizes the costs consisting of the fixed cost, material cost and construction of the potential center cost. To validate this model, a number of test problems are generated, and then its parameters are determined. The presented model is solved by the Lingo software and the associated computational results along with the sensitivity analysis are illustrated. Additionally, the returned products with different demands for one and two products are illustrated. Finally, the remarkable conclusion is presented.

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  The need for flexibility in manufacturing, increased competition, and quick response to meet customer demands in the right time are the necessary subject of discussion in a manufacturing area. There are a number of reasons that affect on a flexible manufacturing system. Scheduling is one significant reason, and affects on a policy that has a direct connection with the dispatching rules. The selection of a rule can be based on several criteria, in which each criterion influences the interactions between them. Thus, a model for the analytical network process (ANP) is needed to find an appropriate dispatching rule. Also, due to the problem nature and uncertainty in the process of pairwise comparison and interactions between the criteria, as well as the selection of dispatching rules, there is no single exact method to be used for solving the presented model. Therefore, considering the existing characteristics in multi-criteria decision making (MCDM) under uncertainty, the ANP model with the interval-valued intuitionistic fuzzy set is used. Then selection of the dispatching rules considering the view of industry experts is done. Finally, the appropriate ranking for this selection is proposed.    

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The hub location decision is a long term investment and any changes in it take considerable time and money. In real situations, some parameters are uncertain hence, deterministic models cannot be more efficient. The ability of two-stage stochastic programming is to make a long-term decision by considering effects of it in short term decisions simultaneously. In the two-stage stochastic programming for hub location problems, the location is decided in the first stage and optimal flow allocations are determined in the second stage. In this paper, the two-stage stochastic programming is described and then a practical stochastic model is employed for determining hub locations in the Iranian aviation. Also, a survey of the model under fuel subsidy omission is conducted using extended two-stage stochastic programming. Demand and the cost of resources (fuel) are considered uncertain in this study. The results show Tehran, Mashhad, Isfahan, Shiraz and Yazd can be hubs in the air network of Iran.