this study is focused on developing an integrated optimization-simulation based genetic algorithm model (iosga) to develop the operational policies for a multi-purpose reservoir system. the objective function of the optimization model is considered to be a linear function of reliability (rel), resiliency (res), and vulnerability (vul) of the river-reservoir system. genetic algorithm (ga) is emp...

This paper presents a methodology for design of instrumentation sensor networks in non-linear chemical plants. The method utilizes a robust extended Kalman filter approach to provide an efficient dynamic data reconciliation. A weighted objective function has been introduced to enable the designer to incorporate each individual process variable with its own operational importance. To enhance...

Finding the best weights of the state variables and the control variables in the objective function of a linear-quadratic control problem is considered. The weights of these variables are considered as two diagonal matrices with appropriate size and so the objective function of the control problem becomes a function of the diagonal elements of these matrices. The optimization problem which is d...

In this paper, power distribution planning (PDP) considering distributed generators (DGs) is investigated as a dynamic multi-objective optimization problem. Moreover, Monte Carlo simulation (MCS) is applied to handle the uncertainty in electricity price and load demand. In the proposed model, investment and operation costs, losses and purchased power from the main grid are incorporated in the f...

In this paper, a bi-objective mixed-integer linear optimization model for Closed-loop Supply Chain Network Design Problem (CLSCND) is developed. The proposed model includes both the forward and reverse directions and includes different types of facilities, namely, manufacturing/remanufacturing centers, warehouses, and disassembly centers. The first objective function tried to minimize the total...

in the real world, risk and uncertainty are two natural properties in the implementation of mega projects. most projects fail to achieve the pre-determined objectives due to uncertainty. a linear integer programming optimization model was used in this work to solve a problem in order to choose the most appropriate risk responses for the project risks. a mathematical model, in which work structu...