Sharif Digital Repository

Usually, resources are short in supply when earthquakes occur. In such emergency situations, disaster relief organizations must use these scarce resources efficiently to achieve the best possible emergency relief. This paper therefore proposes a multi-objective, multi-mode, multi-commodity, and multi-period stochastic model to manage the logistics of both commodities and injured people in the earthquake response. Also, a robust approach is developed and used to make sure that the distribution plan performs well under the various situations that can follow an earthquake. Afterwards, it proposes a solution methodology according to hierarchical objective functions and uses it to illustrate the... 

This paper proposes a stochastic mixed-integer programming (SMIP) model for the reliability-constrained unit commitment (RCUC) problem. The major objective of the paper is to examine both features of accuracy and efficiency of the proposed SMIP model of RCUC. The spinning reserve of generating units is considered as the only available reserve provision resource; however, the proposed formulation can be readily extended to comprise the other kind of reserve facilities. Expected load not served (ELNS) and loss of load probability (LOLP) are accommodated as the reliability constraints. Binding either or both reliability indices ensures the security of operation incorporating the stochastic... 

In this article, the state estimation for Automotive Slip Angle considering the measurement noise in sensor is addressed. Realtime measurement of the slip angle is applicable to many active vehicle safety applications, such as rollover prevention and yaw stability control. As the sensors that measure slip angle directly are expensive, the method to extract slip angle from other available sensors in vehicle is considered. First from the simplified nonlinear dynamic system of vehicle, a Piecewise Affine (PWA) model with calculated uncertainties is obtained. The uncertainties are the result of nonlinear system deviation from PWA model. Then using the PWA model, a Stochastic Robust Hybrid... 

Particle capture at porous media in cross-flow microfiltration is studied to investigate permeability reduction as a function of membrane pore size and particle size distribution. A new model in pore scale and its pertinent mathematical expressions, which consider pore and particle size distribution, are provided. Permeability reduction of the membrane because of size exclusion during particulate suspension flow was predicted using the developed model. It is assumed that the size exclusion is the dominant mechanism of particle retention causes pore blocking and permeability reduction in the porous media.The exact analytical solution of the stochastic model for size exclusion is used to... 

In unreliable supply environments, the strategy of pooling lead time risks by splitting replenishment orders among multiple suppliers simultaneously is an attractive sourcing policy that has captured the attention of academic researchers and corporate managers alike. While various assumptions are considered in the models developed, researchers tend to overlook an important inventory category in order splitting models: deteriorating items. In this paper, we study an order splitting policy for a retailer that sells a deteriorating product. The inventory system is modelled as a continuous review system (s, Q) under stochastic lead time. Demand rate per unit time is assumed to be constant over... 

Increasing the social welfare and achieving real competitive markets are the main purposes of consumers participation in electricity markets. Hence, Demand Response Programs (DRPs) have been designed to consider the consumers participation. One of these programs named Emergency Demand Response Program (EDRP) is based on consumers' responses to high electricity prices and to the incentives that are paid by Independent System Operators (ISOs) in the critical hours. In this paper, a model has been proposed for EDRP participation in the Stochastic Security Constrained Unit Commitment (SCUC) program. Both the spinning reserve and the demand side reserve, which is modeled as EDRP, are taken into... 

In this paper, particle deposition in the upper airways and five lobes of a human lung is simulated. The simulation is based on a stochastic lung model, derived from detailed morphometric measurements. Pathways are simulated using Monte Carlo methods consequently the whole structure changes both stochastically and statistically in each simulation. In this investigation the termination phenomena is a function of each daughter's diameter which best satisfies the lung's morphometry. Complementary to the previous available assumptions, i.e. flow divisions according to the ratio of daughter's cross sections or distal volumes, in this investigation flow rates are computed in an upward manner... 

Stochastic simulation is carried out to investigate intracellular viral reaction kinetics and the time evolution of the average particle number ( N̄) and coefficient variation (CV) for genome, template, and structural protein. The coefficient variation of these components is found to be ordered as: CV template > CV structural protein > CVgenome. The average particle number is also calculated via a deterministic approach. The magnitude value of the difference between the stochastic and deterministic approaches is found to be N̄ template ̃ N̄ structural protein > N̄ genome. The Poisson algorithm has been used to investigate the number of particles in the dynamics of intracellular viral... 

In this paper, a multiproduct multi-chance constraint stochastic inventory control problem is considered, in which the time-periods between two replenishments are assumed independent and identically distributed random variables. For the problem at hand, the decision variables are of integer-type, the service-level is a chance constraint for each product, and the space limitation is another constraint of the problem. Furthermore, shortages are allowed in the forms of fuzzy random quantities of lost sale that are backordered. The developed mathematical formulation of the problem is shown to be a fuzzy random integer-nonlinear programming model. The aim is to determine the maximum level of... 

In this paper we develop a stochastic programming approach to solve a multi-period multi-product multi-site aggregate production planning problem in a green supply chain for a medium-term planning horizon under the assumption of demand uncertainty. The proposed model has the following features: (i) the majority of supply chain cost parameters are considered; (ii) quantity discounts to encourage the producer to order more from the suppliers in one period, instead of splitting the order into periodical small quantities, are considered; (iii) the interrelationship between lead time and transportation cost is considered, as well as that between lead time and greenhouse gas emission level; (iv)... 

A new mathematical model for the capacitated multi-facility location-allocation problem with probabilistic customers' locations and demands is developed in this article. The model is formulated into the frameworks of the expected value model (EVM) and the chance-constrained programming (CCP) based on two different distance measures. In order to solve the model, two hybrid intelligent algorithms are proposed, where the simplex algorithm and stochastic simulation are the bases for both algorithms. However, in the first algorithm, named SSGA, a special type of genetic algorithm is combined and in the second, SSVDO, a vibration-damping optimisation (VDO) algorithm is united. The Taguchi method... 

Production planning is one of the most important issues in manufacturing. The nature of this problem is complex and therefore researchers have studied it under several and different assumptions. In this paper, applied production planning problem is studied in a general manner and it is assumed that there exists an optimal control problem that its production planning strategy is a digital controller and must be optimized. Since this is a random problem because of stochastic values of sales in future, it is modeled as a stochastic dynamic programming and then it is transformed to a linear programming model using successive approximations. Then, it is proved that these two models are... 

This paper presents a particle swarm optimization (PSO) based fuzzy stochastic long term approach for determining optimum location and size of distributed energy resources (DERs). The Monte Carlo simulation method is used to model the uncertainties associated with long-term load forecasting. A proper combination of several objectives is considered in the objective function. Reduction of loss and power purchased from the electricity market, loss reduction in peak load level, and reduction in voltage deviation are simultaneously considered as the objective functions. At first these objectives are fuzzified and designed to be comparable with each other, then they are introduced to a PSO... 

Different sources of uncertainty in power systems, i.e., the uncertainties associated with bus loading and component availability is reflected in uncertainties in different system variables through system physical and economical relationships. A stochastic power flow algorithm can be used to model the stochastic nature of power systems. The algorithm introduced in this paper calculates the probability density function (pdf) of marginal prices of different market services. These pdfs provide the market participant with some valuable information to reduce the risk of their decisions and actions. The algorithm linearizes the optimal power flow formulation and uses the Gram-Charlier method to... 

Particle capture at porous media in cross-flow microfiltration is studied to investigate permeability reduction as a function of membrane pore size and particle size distribution. A new model in pore scale and its pertinent mathematical expressions, which consider pore and particle size distribution, are provided. Permeability reduction of the membrane because of size exclusion during particulate suspension flow was predicted using the developed model. It is assumed that the size exclusion is the dominant mechanism of particle retention causes pore blocking and permeability reduction in the porous media.The exact analytical solution of the stochastic model for size exclusion is used to... 

In this research, minimizing the expected number of tardy jobs in a dynamic m machine flow-shop scheduling problem, i.e.,FM|r j|E[∑Uj] is investigated. It is assumed that the jobs with deterministic processing times and stochastic due dates arrive randomly to the flow-shop cell. The due date of each job is assumed to be normally distributed with known mean and variance. A dynamic method is proposed for this problem by which the m machine stochastic flow-shop problem is decomposed into m stochastic single-machine sub-problems. Then, each sub-problem is solved as an independent stochastic single-machine scheduling problem by a mathematical programming model. Comparison of the proposed method... 

Usually, resources are short in supply when earthquakes occur. In such emergency situations, disaster relief organizations must use these scarce resources efficiently to achieve the best possible emergency relief. This paper therefore proposes a multi-objective, multi-mode, multi-commodity, and multi-period stochastic model to manage the logistics of both commodities and injured people in the earthquake response. Also, a robust approach is developed and used to make sure that the distribution plan performs well under the various situations that can follow an earthquake. Afterwards, it proposes a solution methodology according to hierarchical objective functions and uses it to illustrate the... 

PV generation variability and uncertainty significantly influence operation of the power systems with high penetration of PV sources. The potential impact of distributed PV generation on ramp rate requirements in the IEEE 24-bus system is evaluated in this paper. PV generation and load are, here, probabilistically modeled using actual data and curve fitting approach. Probabilistic unit commitment (UC) based on unit de-commitment method combined with two point estimate method (2-PEM) is used to determine the ramp rate required to compensate for the PV power fluctuations. The proposed method considers stochastic factors and their effects on the dispatch results. Two scenarios are studied to... 

In this paper, the Extended Kalman filtering (EKF) approach has been used to infer gene regulatory networks using time-series gene expression data. Gene expression values are considered stochastic processes and the gene regulatory network, a dynamical nonlinear stochastic model. Using these values and a modified Kalman filtering approach, the model's parameters and consequently the interactions amongst genes are predicted. In this paper, each gene-gene interaction is modeled using a linear term, a nonlinear one, and a constant term. The linear and nonlinear term coefficients are included in the state vector together with the gene expressions' true values. Through the extended Kalman... 

A deterministic energy supply model with bottom-up structure has limited capability in handling the uncertainties. To enhance the applicability of such a model in an uncertain environment two main issues have been investigated in the present paper. First, a binomial lattice is generated based on the stochastic nature of the source of uncertainty. Second, an energy system model (ESM) has been reformulated as a multistage stochastic problem. The result of the application of the modified energy model encompasses all uncertain outcomes together and enables optimal timing of capacity expansion. The performance of the model has been demonstrated with the help of a case study. The case study has...