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While the usual assumptions in multiperiodic inventory control problems are that the orders are placed either at the beginning of each period (periodic review) or depending on the inventory level they can happen at any time (continuous review), in this paper we assume the periods between two replenishments of several products are identical and independent random variables. For the problem at hand, the order quantities (decision variables) are of integertype and there are two kinds of space and service level constraints for each product. A model of the problem is first developed in which a combination of backorder and emergency orders is considered for the shortages, and the costs are... 

Multi-periodic inventory control problems are mainly studied by employing one of two assumptions. First, the continuous review, where depending on the inventory level, orders can happen at any time, and next the periodic review, where orders can only be placed at the beginning of each period. In this paper, we relax these assumptions and assume the times between two replenishments are independent random variables. For the problem at hand, the decision variables (the maximum inventory of several products) are of integer-type and there is a single space-constraint. While demands are treated as fuzzy numbers, a combination of back-order and lost-sales is considered for the shortages. We... 

This paper proposes a new coordinated voltage control scheme to ensure voltage security of power systems. The scheme schedules reactive power injection from VAR sources, including synchronous generators and condensers, capacitor banks, switchable reactors and FACTS devices, to ensure desired loading margin of power systems for a given horizon of time. The problem is treated as voltage security constrained multi-period optimal reactive power flow (VSC-MPORPF). To incorporate scheduling of both continuous and discrete VAR sources, the VSC-MPORPF is formulated as a mixed-integer nonlinear programming problem, and is solved using generalized Benders decomposition (GBD). Multi-period formulation... 

In rail transportation, there have been several attempts to determine the best routes for shipments (a number of cars with the same origin-destination) through the network. Shipments enter into several intermediate yards on their routes to separate and regroup shipments into new trains. Most of time, every entering into a yard includes excessive delay for shipments; therefore it is an ideal plan that each shipment has been transported by an exclusive train service. Mainly because of restriction on a number of running trains, this plan cannot be adapted in most cases. Finding the optimal route over the rail network with above and other common constraints would be handled by railroad blocking... 

This article presents a new model for pricing a new product considering a skimming pricing strategy in the presence of competition. We consider two periods for price setting, including skimming and an economy period. The problem is to decide on skimming as well as economy price, in order to maximize total profit. The derived model is a non-linear programming model and we have analyzed the structure and properties of an optimal solution to develop a solution method. Analytical results, as well as managerial insights, are presented by mathematical and numerical analyses  

In this study, the optimal burn time for low-thrust impulsive propulsion systems is investigated to raise the perigee altitude of a low-Earth orbit. The maneuver is done using spin-stabilized attitude control and impulsive thrusting system for a time interval centered about apogee point. On the one hand, the low value of the thrust level causes more burn time needed to accomplish the transfer. This, in turn, will cause more thrust loss due to the deviation between the thrust axis (spin axis) and the velocity vector of the satellite. On the other hand, for small thrust duration, the transfer needs more revolutions around the Earth and more travel in lower altitudes with dense atmosphere and... 

We present a structured algorithm for solving constrained nonlinear least squares problems, and establish its local two-step Q-superlinear convergence. The approach is based on an 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. We discuss the comparative results of the testing of our programs and three nonlinear programming codes from KNITRO on some randomly generated test problems due to Bartels and Mahdavi-Amiri. The results indeed confirm the... 

We consider a multi-facility location problem in the presence of a line barrier with the starting point of the barrier uniformly distributed. The objective is to locate n new facilities among m existing facilities minimising the summation of the weighted expected rectilinear barrier distances of the locations of new facilities and new and existing facilities. The proposed problem is designed as a mixed-integer nonlinear programming model, conveniently transformed into a mixed-integer quadratic programming model. The computational results show that the LINGO 9.0 software package is effective in solving problems with small sizes. For large problems, we propose two meta-heuristic algorithms,... 

In this paper, a multiproduct inventory control problem is considered in which the periods between two replenishments of the products are assumed independent random variables, and increasing and decreasing functions are assumed to model the dynamic demands of each product. Furthermore, the quantities of the orders are assumed integer-type, space and budget are constraints, the service-level is a chance-constraint, and that the partial back-ordering policy is taken into account for the shortages. The costs of the problem are holding, purchasing, and shortage. We show the model of this problem is an integer nonlinear programming type and to solve it, a harmony search approach is used. At the... 

In this paper, a multi-product multi-chance constraint joint single-vendor multi-buyers inventory problem is considered in which the demand follows a uniform distribution, the lead-time is assumed to vary linearly with respect to the lot size, and the shortage in combination of backorder and lost-sale is assumed. Furthermore, the orders are placed in multiple of packets, there is a limited space available for the vendor, there are chance constraints on the vendor service rate to supply the products, and there is a limited budget for each buyer to purchase the products. While the elements of the buyers' cost function are holding, shortage, order and transportation costs, the set up and... 

Aximum coverage location problem is considered in this study. Extension of this problem is investigated for situations that coverage areas are elliptical; these ellipses can locate anywhere on the plane with any angle. Mixed integer nonlinear programming (MINLP) is applied for formulation. This problem can be used in many practical situations such as locating wireless transmitter towers. A heuristic algorithm named MCLPEA for solving this problem was designed. This algorithm can produce very good results in efficient running time. Finally, the comparison of the results for this study was carried done  

In this paper, the problem of Optimal Trajectory Planning for a high speed planing boat under nonlinear equality and inequality path constraints, is addressed. First, a nonlinear mathematical model of the craft's dynamic is constructed. To solve a trajectory optimization problem, we can utilize the indirect or direct methods. In the indirect methods, the maximum principle of Pontryagin is used to transform the optimal control problem into Euler-Lagrange equations, on the other hand, in the direct methods it is necessary to transcribe the optimal control problem into a nonlinear programming problem (NLP) by discretization of states and controls. The resulted NLP can be solved by... 

In this paper, a multi-buyer multi-vendor supply chain problem is considered in which there are several products, each buyer has limited capacity to purchase products, and each vendor has warehouse limitation to store products. In this chain, the demand of each product is stochastic and follows a uniform distribution. The lead-time of receiving products from a vendor to a buyer is assumed to vary linearly with respect to the order quantity of the buyer and the production rate of the vendor. For each product, a fraction of the shortage is backordered and the rest are lost. The ordered product quantities are placed in multiple of pre-defined packets and there are service rate constraints for... 

In this paper, a new algorithm for solving constrained nonlinear programming problems is presented. The basis of our proposed algorithm is none other than the necessary and sufficient conditions that one deals within a discrete constrained local optimum in the context of the discrete Lagrange multipliers theory. We adopt a revised particle swarm optimization algorithm and extend it toward solving nonlinear programming problems with continuous decision variables. To measure the merits of our algorithm, we provide numerical experiments for several renowned benchmark problems and compare the outcome against the best results reported in the literature. The empirical assessments demonstrate that... 

To stay competitive in the new dynamic market having large fluctuations in product demand, manufacturing companies must use systems that not only produce their goods with high productivity but also allow for rapid response to market changes. Reconfigurable manufacturing system (RMS) is a new paradigm that enables manufacturing systems to respond quickly and cost effectively to market demand. In other words, RMS is a system designed from the outset, for rapid changes in both hardware and software components, in order to quickly adjust its production capacity to fluctuations in market demand and adapt its functionality to new products. The effectiveness of an RMS depends on implementing its... 

Cost is one of the most essential factors that influence many decisions taken in the distribution system planning. In general, cost can be defined as everything that should be sacrificed to gain the desired results. This paper proposes a new two-stage methodology for distributed generation (DG) placement as an attractive option for distribution system planner. This method aims to minimize cost and maximize total system benefit (TSB). Optimal placement and size are obtained from total cost minimization mathematical problem which is solved in the first stage. For each DG cost characteristics and for each investment payback time, there is an optimal location and size. Then the optimal DG... 

We consider nonlinear optimization problems constrained by a system of fuzzy relation equations. The solution set of the fuzzy relation equations being nonconvex, in general, conventional nonlinear programming methods are not practical. Here, we propose a genetic algorithm with max-product composition to obtain a near optimal solution for convex or nonconvex solution set. Test problems are constructed to evaluate the performance of the proposed algorithm showing alternative solutions obtained by our proposed model  

We are concerned with a capacitated location-multi allocation-routing problem in a road network with flexible travel times. It is assumed that all links are two-way and capacities of the server nodes and arcs for accepting of population are limited. The aim of our work is to find numbers and locations of server nodes, allocation of the existing population in existing demand nodes on the network to the servers and the allocation of existing population in each node to different routes to determine the decided server for each member so that total transportation time is minimized. Here, two basic concepts are considered: multi allocation and flexible travel times. The concept of multi allocation... 

Osmotic power generation is one of the cleaner and sustainable methods for energy generation. This paper presents a study on the optimal size and design of pressure retarded osmosis (PRO) power plant as a viable source of renewable energy in the selected site in Bahmanshir river of Iran. The optimal sizing and design problem is formulated as a Non-Linear Programming (NLP) optimization problem and solved using the standard optimization software titled generalized algebraic modeling system (GAMS). The objective function is minimizing the total cost while considering the technical and economic constraints. Optimization results show that the optimal capacity of the PRO osmotic power plant is... 

The main focus of this paper is to develop a model considering some significant aspects of real-world supply chain production planning approved by industries. To do so, we consider a supply chain (SC) model, which contains multiple suppliers, multiple manufactures and multiple customers. This model is formulated as a fuzzy multi objective mixed-integer nonlinear programming (FMOMINLP) to address a comprehensive multi-site, multi-period and multi-product aggregate production planning (APP) problem under uncertainty. Four conflicting objectives are considered in the presented model simultaneously, which are (i) to minimize the total cost of the SC (production costs, workforce wage,...