Sharif Digital Repository

This paper proposes a multi-item economic order quantity model with imperfect items in supply deliveries. The inspection process to classify the items is not perfect and involves two types of error: Type-I and Type-II. To cope with the uncertainty involved in real-world applications and to bring the problem closer to reality, operational constraints are assumed stochastic. The aim is to determine the optimal order and back order sizes of the items in order to achieve maximum total profit. As the proposed mathematical model is a constrained nonlinear programming, three different solution methods including an exact method named the interior-point and two novel meta-heuristics named grey wolf... 

This paper examines the problem of determining optimal sensors trajectories for localization of a moving radio source based on Time Difference of Arrival (TDOA) and Frequency Difference of Arrival (FDOA) measurements in situations in which sensors are constrained both in their movements and regions of operation. By considering the movement of the source and constrained movement of the sensors, a constraint problem is formed which is solved to determine optimal trajectories of the sensors for source tracking. The validity of the proposed algorithm is assessed by two different simulation scenarios and the results verify its proper operation with estimation error decreasing in consecutive steps... 

In this paper, a multiproduct single vendor-single buyer supply chain problem is investigated based on the economic production quantity model developed for the buyer to minimize the inventory cost. The model to be more applicable for real-world supply chain problems contains five stochastic constraints including backordering cost, space, ordering, procurement, and available budget. The objective is to find the optimal order quantities of the products such that the total inventory cost is minimized while the constraints are satisfied. The recently-developed sequential quadratic programming (SQP), as one of the best optimization methods available in the literature, is used to solve the... 

We study a capacitated multi-facility location-allocation problem in which the customers have stochastic demands based on Bernoulli distribution function. We consider the capacitated sub-sources of facilities to satisfy demands of customers. In the discrete stochastic problem, the goal is to find optimal locations of facilities among candidate locations and optimal allocations of existing customers to operating facilities so that the total sum of fixed costs of operating facilities, allocation cost of the customers, expected values of servicing and outsourcing costs is minimized. The model is formulated as a mixed-integer nonlinear programming problem. Since finding an optimal solution may...