Data envelopment analysis (DEA) is a common technique in measuring the relative efficiency of a set of decision making units (DMUs) with multiple inputs and multiple outputs. ‎‎Standard DEA models are ‎‎quite limited models‎, ‎in the sense that they do not consider a DMU ‎‎at different times‎. ‎To resolve this problem‎, ‎DEA models with dynamic ‎‎structures have been proposed‎.‎In a recent pape...

To design a group layout of a cellular manufacturing system (CMS) in a dynamic environment, a multi-objective mixed-integer non-linear programming model is developed. The model integrates cell formation, group layout and production planning (PP) as three interrelated decisions involved in the design of a CMS. This paper provides an extensive coverage of important manufacturing features u...

closed-loop supply chain network design is a critical issue due to its impact on both economic and environmental performances of the supply chain. in this paper, we address the problem of designing a multi-echelon, multi-product and capacitated closed-loop supply chain network. first, a mixed-integer linear programming formulation is developed to maximize the total profit. the main contribution...

One of the most complicated decision making problems for managers is the evaluation of bank performance, which involves various criteria. There are many studies about bank efficiency evaluation by network DEA in the literature review. These studies do not focus on multi-level network. Wu (Eur J Oper Res 207:856–864, 2010) proposed a bi-level structure for cost efficiency at the first time. In t...

The previous research on cross-training mainly focused on productive efficiency. However, enhancing labor’s satisfaction of tasks is as much important as improving production performance. This paper addresses a new cross-training policy for an assembly cell from the point of view of humanization. A multi-objective 0-1 integer programming model is presented to implement the crosstraining policy ...

A multiobjective binary integer programming model for R&D project portfolio selection with competing objectives is developed when problem coefficients in both objective functions and constraints are uncertain. Robust optimization is used in dealing with uncertainty while an interactive procedure is used in making tradeoffs among the multiple objectives. Robust nondominated solutions are generat...

Optimization problems are not only formed into a linear programming but also nonlinear programming. In real life, often decision variables restricted on integer. Hence, came the nonlinear programming. One particular form of nonlinear programming is a convex quadratic programming which form the objective function is quadratic and convex and linear constraint functions. In this research designed ...

A three-level relief chain including a number of suppliers in fixed locations, candidate distribution centers and affected areas at certain points are considered. A mixed integer nonlinear programming model is proposed for open transportation location routing problem by considering split delivery of demand. To solve a realistic problem, foregoing parameters are considered as fuzzy in our propos...

We present a new model and a new approach for solving fuzzylinear programming (FLP) problems with various utilities for the satisfactionof the fuzzy constraints. The model, constructed as a multi-objective linearprogramming problem, provides flexibility for the decision maker (DM), andallows for the assignment of distinct weights to the constraints and the objectivefunction. The desired solutio...

This paper discussed the scheduling problem of outpatients in a radiology center with an emphasis on priority. To more compatibility to real-world conditions, we assume that the elapsed times in different stages to be uncertain that follow from the specific distribution function. The objective is to minimize outpatients’ total spent time in a radiology center. The problem is formulated as a fle...