We consider a distributionally robust optimization problem where the ambiguity set of probability distributions is characterized by a tractable conic representable support set and expectation constraints. Specifically, we propose and motivate a new class of infinitely constrained ambiguity sets in which the number of expectation constraints could potentially be infinite. We show how the infinit...

optimization of maintenance resources to maximize the system availability is a major concern in different manufacturing systems. therefore, a lot of effort is put to construct optimization models to reach the maximum availability level and to reduce the costs of lack of availability. however, despite these efforts, data uncertainty in the real world problems was neglected in proposed models whi...

in this paper, firstly by using a mixed linear programming a new model of locating facilities with limited capacity is presented to design a closed-loop supply chain in a multi-product and multi-period mode. then, using a robust optimization approach, the proposed model decreases in non-deterministic expansion. the results show that the proposed model can handle facility capacity in a closed lo...

There are many real problems in which multiple responses should be optimized simultaneously by setting of process variables. One of the common approaches for optimization of multi-response problems is desirability function. In most real cases, there is a correlation structure between responses so ignoring the correlation may lead to mistake results. Hence, in this paper a robust approach based ...

perishability of blood products as well as uncertainty in demand amounts complicate the management of blood supply for blood centers. this paper addresses a mixed-integer linear programming model for blood platelets production planning while integrating the processes of blood collection as well as production/testing, inventory control and distribution. whole blood-derived production methods for...

optimization models have been used to support decision making in production planning for a long time. however, several of those models are deterministic and do not address the variability that is present in some of the data. robust optimization is a methodology which can deal with the uncertainty or variability in optimization problems by computing a solution which is feasible for all possible ...

Lean manufacturing is a strategic concern for companies which conduct mass production and it has become even more significant for those producing in a project-oriented way by modularization.  In this paper, a bi-objective optimization model is proposed to design and plan a supply chain up to the final assembly centre. The delivery time and the quality in the procurement and low fluctuation of t...

Optimization of reservoir parameters is an important issue in petroleum exploration and production. The Ant Colony Optimization(ACO) is a recent approach to solve discrete and continuous optimization problems. In this paper, the Ant Colony Optimization is usedas an intelligent tool to estimate reservoir rock properties. The methodology is illustrated by using a case study on shear wave velocity...