Sharif Digital Repository

In this study, we consider a capacitated location–multi-allocation–routing problem with population-dependent random travel times. The objective is to find appropriate locations as server locations among the candidate locations, allocate the existing population in each demand node to server locations, and determine the movement path of each member to reach its corresponding server with respect to the simultaneous change of the random travel times so that the expected total transportation time is minimized. In our study, the concept of population-dependent random travel times incurs two issues: (1) consideration of some random factors in computing the travel times and (2) impact of the... 

In this paper, a design of the supply chain distributer-retailer network for a seasonal multiple-product location allocation-inventory control problem in a planning horizon consisting of multiple periods is modeled. The distance between the distributers and retailers are assumed to be Euclidean and square Euclidean while retailers purchase the products from the distributers under all-unit and incremental quantity discount policies. Furthermore, the products are delivered in packets of known size of items and in case of shortage, a fraction of demand is considered backorder and a fraction lost sale. Besides, the distributers store the manufactured products in their warehouses before... 

Abstract In a recent work, Alizadeh et al. (2013) studied a capacitated multi-facility location-allocation problem in which customers had stochastic demands based on the Bernoulli distribution function. Authors considered capacitated sub-sources of facilities to satisfy customer demands. In this discrete stochastic problem, the goal was 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 costs of customers and expected values of servicing and outsourcing costs was minimized. The model was formulated as a mixed-integer nonlinear... 

This paper presents a novel profit-based model for multistage distribution network expansion planning. In the proposed model, some capabilities of the distribution automation system are considered to achieve a plan that is more compatible with the strategic plan towards a smart distribution grid. Moreover, a method for reliability evaluation of a distribution network in the planning studies is proposed. The objective function of the planning problem is the net present value of the company's profit. The problem is solved by employing the genetic algorithm approach as a promising technique in solving the mixed-integer nonlinear programming problem. The proposed method is evaluated on an... 

An accurate estimation of aquifer hydraulic parameters is required for groundwater modeling and proper management of vital groundwater resources. In situ measurements of aquifer hydraulic parameters are expensive and difficult. Traditionally, these parameters have been estimated by graphical methods that are approximate and time-consuming. As a result, nonlinear programming (NLP) techniques have been used extensively to estimate them. Despite the outperformance of NLP approaches over graphical methods, they tend to converge to local minima and typically suffer from a convergence problem. In this study, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) methods are used to identify... 

We present a combined trust region-line search structured algorithm for solving constrained nonlinear least-squares problems. The approach is based on adaptive structured scheme due to Mahdavi-Amiri and Bartels of the exact penalty method of Coleman and Conn for nonlinearly constrained optimization problems. The structured adaptation also makes use of the ideas of Nocedal and Overton for handling quasi-Newton updates of projected Hessians. For robustness, we propose a new penalty parameter updating strategy and a specific line search strategy within the trust region, taking account of the least-squares objective and special structured considerations for the approximate projected... 

Nowadays the maintenance of the deteriorating structures is an important subject in industry and research. Due to the limitations of the budget and time, the optimization algorithms have been used widely to determine the best maintenance strategies to provide the more economical structures. On the other side, the Less life-cycle cost will result in less safe structures. As safety is a vital criterion for the users of a structural system, there is a severe need to make a suitable trade-off between cost and safety. So, the optimal maintenance strategies are those that fulfill both the safety and the economical requirements. In this paper, the reliability of the structural system is selected to... 

In this paper a new model is proposed for the integrated problem of supply chain network designing and assembly line balancing under demand uncertainty. In this problem there are three types of entities: manufacturers, assemblers and customers. Manufacturers provide assemblers with components and assemblers use these components to produce the final products and satisfy the demand of the customers. This problem involves determining the location of manufacturers and assemblers in the network, balancing the assembly lines, and transportation of materials and products throughout the network. A mixed integer nonlinear programming formulation based on two stage stochastic programming method is... 

This paper presents a bi-objective vendor managed inventory (BOVMI) model for a supply chain problem with a single vendor and multiple retailers, in which the demand is fuzzy and the vendor manages the retailers' inventory in a central warehouse. The vendor confronts two constraints: number of orders and available budget. In this model, the fuzzy demand is formulated using trapezoidal fuzzy number (TrFN) where the centroid defuzzification method is employed to defuzzify fuzzy output functions. Minimizing both the total inventory cost and the warehouse space are the two objectives of the model. Since the proposed model is formulated into a bi-objective integer nonlinear programming (INLP)... 

Bi-objective optimization of a multi-product multi-period three-echelon supply-chain-network problem is aimed in this paper. The network consists of manufacturing plants, distribution centers (DCs), and customer nodes. To bring the problem closer to reality, the majority of the parameters in this network including fixed and variable costs, customer demand, available production time, set-up and production times, all are considered stochastic. The goal is to determine the quantities of the products produced by the manufacturing plants in different periods, the number and locations of the warehouses, the quantities of products transported between the supply chain entities, the inventory of... 

This paper develops an economic production quantity (EPQ) inventory model for a multiproduct single-machine lot-sizing problem with nonconforming items including scrap and rework, where reworks are classified into several groups based on failure severity. In this inventory model, shortage is allowed and is backordered. The aim is to determine the optimal period length, the lot size, and the allowable shortage of each product so as the total cost, including setup, production, warehouse construction, holding, shortage, reworking, and disposal is minimized. Besides, the available total budget is scarce and that there is a lower bound on the service level of each product. While the convexity is... 

We concern with both time and cost optimization in an automated manufacturing system. In our proposed system, material handling is carried out by automated guided vehicles and robots for the manufacturing functions. In this way, defect rates, breakdown times, waiting time, processing time, and certain other parameters are not expected to be deterministic. Therefore, we apply stochastic programming to optimize the production time and material handling cost. The proposed stochastic program is a nonlinear model, for this reason we apply a successive linear programming (SLP) technique for its optimization. Numerical test results point to the inefficacy of the proposed optimization method for... 

A new nonlinear optimization method for parameter estimation in Michaelis-Menten equation has been developed. This method is based on a special mathematical form of the Michaelis-Menten equation to finding the best fit of the linear plot of R versus S/(S + Km) where R, S, and Km are the reaction rate, concentration of substrate, and the Michaelis-Menten constant, respectively. By setting the intercept of this line to zero, the proper Km will be obtained and the slope would give the saturation rate, Vmax. As a result, a nonlinear, two-parameter optimization is simplified into finding the roots of a nonlinear equation. Generated data sets were used... 

In this paper, we study a pricing-inventory model with multiple interdependent products and stochastic demand. In the relevant literature, there are many researches that try to optimize the inventory or price independently and also optimizing joint inventory and pricing problems for single product. But joint optimization of inventory and pricing for multiple interdependent products is relatively new and still there are many potential research gaps in this area. We show that the multiplicative demand form problem, that we develop, is a convex nonlinear programming (NLP) model or is convertible to it. We also provide upper and lower bounds for the additive demand form model  

There are two main assumptions in multiperiodic inventory control problems. The first is the continuous review, where, depending on the inventory level, orders can happen at any time, and the other is the periodic review, where orders can only happen at the beginning of each period. In this paper, these assumptions are relaxed, and the periods between two replenishments are assumed independent and identically distributed random variables. Furthermore, the decision variables are assumed integer-type and that there are two kinds of space and budget constraints. The incremental discounts to purchase products are considered, and a combination of backorder and lost sales are taken into account... 

Wind power is a promising alternative in power generation because of its tremendous environmental and social benefits. Generation scheduling (GS) is more important in a power system integrating wind farms. Unlike conventional power generation sources, wind power generators supply intermittent power because of uncertainty in resource. This paper presents a fuzzy approach to the generation scheduling problem of a GenCo considering uncertainties in parameters or constraints such as load, reserve and available wind power generation. The modeling of constraints is an important issue in power system scheduling. A fuzzy optimization approach is an approach that can be used to obtain the generation... 

While the usual assumptions in multi-periodic inventory control problems are that the orders are placed at the beginning of each period (periodic review) or depending on the inventory level they can happen at any time (continuous review), in this article, we relax these assumptions and assume that the periods between two replenishments of the products are independent and identically distributed random variables. Furthermore, assuming that the purchasing price are triangular fuzzy variables, the quantities of the orders are of integer-type and that there are space and service level constraints, total discount are considered to purchase products and a combination of back-order and lost-sales... 

Integration of wind power generation creates new concerns for operation engineers in a power system. Unlike conventional power generation sources, wind power generators supply intermittent power due to uncertainty in parameters of wind such as its velocity. This paper presents probabilistic model for load and wind power uncertainty which can be used in operation planning (with durations up to one or two years). A stochastic model is proposed to simulate the status of units that are directly affected by the load and wind power generation uncertainties. This paper develops a solution method for generation scheduling of power system, while taking into account the stochastic behavior of the load... 

This paper studies inventory and pricing policies in a non-cooperative supply chain with one supplier and several retailers who are involved in producing, delivering and selling a single product. We consider inventory policies in an information-asymmetric vendor managed inventory. The study consists of different scenarios where a supplier produces the product at the wholesale price to multiple retailers. The retailers also distribute the product in dispersed and independent markets at retail selling prices. The demand rate for each market is a non- decreasing concave function of the marketing expenditures of both local retailers and the manufacturer, but a non-increasing and convex function... 

Calculation of camera projection matrix, also called camera calibration, is an essential task in many computer vision and 3D data processing applications. Calculation of projection matrix using vanishing points and vanishing lines is well suited in the literature; where the intersection of parallel lines (in 3D Euclidean space) when projected on the camera image plane (by a perspective transformation) is called vanishing point and the intersection of two vanishing points (in the image plane) is called vanishing line. The aim of this paper is to propose a new formulation for easily computing the projection matrix based on three orthogonal vanishing points. It can also be used to calculate the...