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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... 

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... 

We propose a robust optimization framework to deal with uncertain component reliabilities in redundancy allocation problems in series-parallel systems. The proposed models are based on linearized versions of standard mixed integer nonlinear programming (MINLP) formulations of these problems. We extend the linearized models to address uncertainty by assuming that the component reliabilities belong to a budgeted uncertainty set, and develop robust counterpart models. A key challenge is that, because the models involve nonlinear functions of the uncertain data, classical robust optimization approaches cannot apply directly to construct their robust optimization counterparts. We exploit problem... 

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 growing economic energy systems, the interdependency of various energy infrastructures has led to a change in countries' policies in their expansion planning of energy networks. In this study, a mixed-integer non-linear programming (MINLP) model is proposed for expansion planning of the multi-carrier systems including electricity and gas distribution networks. The optimal planning determines the best location, time, and alternative for network assets in order to minimise investment costs and reduce losses. Also, as another distinctive feature of this study, given the integration of electricity and gas distribution networks and the complexity of the problem, a new MILP model using... 

This article proposes a multi-objective goal programming based approach with two objectives of maximizing the reliability and minimizing the placement cost of Phasor Measurement Units (PMUs) for full observability in power systems. The weighted sum goal programming formulation incorporates the reliability of individual PMUs and finds a placement to resolve the conflicting objectives of minimum number of PMUs cost-wise and maximum level of system-wide reliability. This multi-objective problem is formulated as a nonlinear goal programming model in which weights are associated with the objectives. The model is solved for several weight scenarios for the IEEE 14, 30, 57 and 118 bus test systems.... 

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... 

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 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... 

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... 

We provide a mixed-integer nonlinear programming (MINLP) model for a location-allocation-routing problem in a transportation network with links carrying the travel times among the nodes in the network. The travel time between two nodes is considered to be intelligent, that is, since the travelling population in a link can affect the travel time, here we consider the impact of the travelling population on the travel time of the link. This way, depending on how the population is distributed in the network, the travel times of the links may change. The problem is to find an optimal locations of server node(s), allocation of existing demand nodes in the network to the server(s) and allocation of... 

While in multi-periodic inventory control problems the usual assumption 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 research, we relax these assumptions and assume that the periods between two replenishments of the products are independent and identically distributed random variables. Furthermore, assuming the purchasing price are triangular fuzzy variables, the quantities of the orders are of integer-type and that there are space, budget and service level constraints, incremental discount is considered to purchase products and a combination of back-order and... 

Purpose: This study aims to deal with supplier selection problem. The supplier selection problem has significantly become attractive to researchers and practitioners in recent years. Many real-world supply chain problems are assumed as multiple objectives combinatorial optimization problems. Design/methodology/approach: In this paper, the authors propose a multi-objective model with fuzzy parameters to select suppliers and allocate orders considering multiple periods, multiple resources, multiple products and two-echelon supply chain. The objective functions consist of total purchase costs, transportation, order and on-time delivery, coverage and the weights of suppliers. Distance-based... 

In this paper, we design and optimise an integrated four-level Supply Chain (SC), which contains a supplier, a producer, a wholesaler and multiple retailers. The levels cooperate to make an Integrated SC (ISC) so that the inventory cost is minimised and the reliability is maximised, simultaneously. The model is constrained by real stochastic constraints on total space, number of orders, procurement cost, shortage cost, setup cost and production capacity. An Lp-Metric function converts the reliability function and cost function into a single-objective function to optimise the number of stockpiles and period lengths. The designed ISC is a large-scale Nonlinear Programming (NLP) and hard to... 

In pressurized water reactors, the fuel reloading problem has significant meaning in terms of both safety and economics. An optimal loading pattern is defined as a pattern in which the local power peaking factor (Pq) is lower than a predetermined value during one cycle and the effective multiplication factor (keff) is maximized to extract the maximum energy. This article presents a specialized genetic algorithm for loading pattern design. The tests on well-researched cases have shown that the genetic algorithm is capable of finding better loading patterns than solutions found by direct search methods. However, most of the previous researchers have considered simple fitness (cost) functions;... 

The null-space method (NSM) for solving the nonlinear programming (NLP) is used to transform an indefinite system into a symmetric positive definite one of a smaller dimension. In this paper, an NSM optimises the constrained NLP model of the inventories in multi-level supply chains (SCs). The presented NSM can give a direct method with a predictable level of fill without pivoting, decreasing the number of taken iterations to find the optimum solution. We transform the nonlinear equations into an NLP model, which NSM can solved. We also investigate the suitability of using null-space-based factorisations to derive sparse direct methods. Accordingly, an integrated lot-sizing model of the... 

This paper presents artificial neural network (ANN) meta-models for expensive continuous simulation optimization (SO) with stochastic constraints. These meta-models are used within a sequential experimental design to approximate the objective function and the stochastic constraints. To capture the non-linear nature of the ANN, the SO problem is iteratively approximated via non-linear programming problems whose (near) optimal solutions obtain estimates of the global optima. Following the optimization step, a cutting plane-relaxation scheme is invoked to drop uninformative estimates of the global optima from the experimental design. This approximation is iterated until a terminating condition... 

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... 

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...