多气源天然气管网运行优化问题的混合整数规划模型及其算法

对于多气源天然气管网运行优化问题,文章首先引入了刻画压缩机开关的0-1整数变量,并对非线性的管道压降方程进行了合理的松弛化处理,建立了更符合实际的非线性混合整数规划模型.其次,基于序列线性化的思想,设计了一种求解该模型的序列混合整数线性化算法.最后,在不同规模的天然气管网系统中进行了多方面的对比实验.实验结果表明,新模型及求解算法能够有效降低成本、减少压缩机能耗,并且所需求解时间大大减少.     

基于ε-EGA多准则调整的舰船维修资源配置决策方法与应用

为了提高舰船维修资源配置的科学性、有效性，针对舰船维修目标提出维修战斗力定义，统筹考虑了舰船维修资源配置过程中的财力、人力、物力和技术资源对于资源配置的影响，构建了舰船维修资源配置模型。求解方法上，以军事效益(维修战斗力)最大和维修成本最小为优化目标，将舰船维修资源配置问题转化为混合整数非线性规划模型的多目标寻优问题。在标准遗传算法(SGA)基础上，融合ε约束准则和精英保留策略，构建一种新型ε-EGA的多准则调整算法，搜索获取满意的Pareto解集与前沿。结合企业H的年度舰船维修任务实际进行实证检验，提高优化配置模型结论的科学性，增强模型与实际情况的吻合度。结果表明，ε-EGA多准则调整算法具有良好的适用性和延展性，计算速度快，方案优化度高，而维修资源配置模型对于其他建造工程行业的资源调度、计划安排等工作开展，也具有较强的借鉴意义。     

求解MINLP的几类罚函数方法的分析和探讨

针对混合整数非线性约束优化问题(MINLP)的一般形式,通过罚函数的方法,给出了它的几种等价形式,并证明了最优解的等价性.将约束优化问题转化成更容易求解的无约束非线性优化问题,并把混合整数规划转化成非整数优化问题,从而将MINLP的求解简化为求解一个连续的无约束非线性优化问题,进而可用已有的一般无约束优化算法进行求解.     

乘用车物流运输计划问题的建模研究

首先针对不同类型、数量乘用车的物流运输问题,构建整数线性规划模型,并对模型进行逐层优化求解,通过MATLAB编写通用程序实现计算;在此基础之上,为解决不同目的地的运输要求,采用启发式逐层优化算法进行求解;最后考虑多因素的实际问题,建立分层划分模型,提出构造型分层划分启发式算法求解.计算表明,所建模型计算结果良好,实现了对乘用车物流运输计划问题的优化.     

多指标席位分配模型及其应用

将经典席位分配模型推广,建立了多指标席位分配模型,它是一个有界整数变量非线性规划模型。将模型转化为非线性连续规划模型,因而可用各种具有良好收敛性和收敛速度的求解非线性连续规划的算法求解。给出多指标席位分配模型的一个简单有效的算法。最后实例说明多指标席位分配模型应用更加合理、更加广泛。     

到货不确定的多商品多阶段多折扣的采购与存储问题

考虑一个制造商和多个供应商的采购与存储问题。多个供应商分别提供多种原材料，采用一种折扣方案，或单品全量折扣，或总量全量折扣，或混合全量折扣。制造商根据供应商提供的原材料品种和折扣方案，考虑不能按时到货的情况下，确定订货量，制定运输和仓储方案，以最小化总体运营成本。受运输过程中多种因素的影响，到货时间存在一定的不确定性，由此引出调货问题。用模糊随机变量表示到货率，建立相应的模糊随机数学优化模型，通过建立模糊随机期望值模型的方法将不确定的模糊随机优化模型转化为确定的混合整数非线性规划模型。给出求解该问题的算法——基于核搜索的启发式算法，对算例求解并证明了算法的可行性与有效性。通过数值实验，对相关参数进行分析，给出其经济解释，为管理者决策提供参考。     

整数非线性规划的一种直接搜索寻优算法

本文的工作是将Rosenbrock算法移殖求解整数非线性规划,得到一种求解整数非线性规划的直接搜索寻优算法,该算法只要求函数是可计算的,可适用于实际规划问题。     

基于组合预测的变压器故障诊断模型

为了快速准确地预测出变压器的故障类型,及时做好维修工作,本文提出了一种基于非线性规划的组合预测模型.首先,利用改进的鲸鱼算法优化BP神经网络建立IWOA-BP预测模型;然后,在IWOA-BP预测模型和梯度提升树的基础上,利用非线性规划与遗传算法相结合的方法确定各算法的权系数,再将各算法的结果加权得出组合模型的最终预测结果.通过实例验证,IWOA-BP预测模型的变压器故障预测效果强于BP神经网络、随机森林等多种预测模型,并且利用IWOA-BP预测模型和梯度提升树建立的组合模型,其预测准确率高于组合中任意一种算法.     

计算机指令优化控制模型

为了对计算机指令进行最优控制设计 ,我们建立了解决最优控制的整数线性规划模型 .由于变量较多 ,约束条件全都是线性的 ,目标函数为一次 ,我们采用单纯形法对问题求解 ,整个算法都用 c语言实现 ,并对实例进行了求解 .本模型很好的解决了计算机指令优化控制的问题 ,也适用于其他类似问题 .     

中间品储存约束的多工序批量加工排序问题研究

本文结合生产实际情况，考虑了有限的中间品储存能力所带来的影响，对具有中间品储存约束的多工序批量加工排序问题进行研究。文中利用状态-任务-网络概念和层级模型方法，构建了基于混合整数线性规划的修正排序模型，应用标准优化软件求解。最后用一个算例来说明所构建模型的有效性。     

Efficient MIP formulation for optimal 1-for-N diversity coding

In the paper we consider a communication network that uses diversity coding in order to achieve reliability. Having a set of demands and a network topology we face a problem of optimal routing of the demands and backup trees, and associations between the demands and the backup trees. We present a compact mixed integer programming (MIP) formulation for the optimization problem, which proves to be more efficient than other approaches that can be found in the literature.     

Mixing mixed-integer inequalities

Mixed-integer rounding (MIR) inequalities play a central role in the development of strong cutting planes for mixed-integer programs. In this paper, we investigate how known MIR inequalities can be combined in order to generate new strong valid inequalities.?Given a mixed-integer region S and a collection of valid “base” mixed-integer inequalities, we develop a procedure for generating new valid inequalities for S. The starting point of our procedure is to consider the MIR inequalities related with the base inequalities. For any subset of these MIR inequalities, we generate two new inequalities by combining or “mixing” them. We show that the new inequalities are strong in the sense that they fully describe the convex hull of a special mixed-integer region associated with the base inequalities.?We discuss how the mixing procedure can be used to obtain new classes of strong valid inequalities for various mixed-integer programming problems. In particular, we present examples for production planning, capacitated facility location, capacitated network design, and multiple knapsack problems. We also present preliminary computational results using the mixing procedure to tighten the formulation of some difficult integer programs. Finally we study some extensions of this mixing procedure. Received: April 1998 / Accepted: January 2001?Published online April 12, 2001     

On a pair of nonlinear mixed integer programming problems

We consider maximin and minimax nonlinear mixed integer programming problems which are nonsymmetric in duality sense. Under weaker (pseudo-convex/pseudo-concave) assumptions, we show that the supremum infimum of the maximin problem is greater than or equal to the infimum supremum of the minimax problem. As a particular case, this result reduces to the weak duality theorem for minimax and symmetric dual nonlinear mixed integer programming problems. Further, this is used to generalize available results on minimax and symmetric duality in nonlinear mixed integer programming.     

A disjunctive cutting plane procedure for general mixed-integer linear programs

In this paper we develop a cutting plane algorithm for solving mixed-integer linear programs with general-integer variables. A novel feature of the algorithm is that it generates inequalities at all γ-optimal vertices of the LP-relaxation at each iteration. The cutting planes generated in the procedure are found by considering a natural generalization of the 0-1 disjunction used by Balas, Ceria, and Cornuéjols in the context of solving binary mixed-integer linear programs [3, 4]. Received: January 1999 / Accepted: March 2000?Published online December 15, 2000     

Regulation of Overlaps in Technology Development Activities

In this paper, we present an algorithm for the solution of multiparametric mixed integer linear programming (mp-MILP) problems involving (i) 0-1 integer variables, and, (ii) more than one parameter, bounded between lower and upper bounds, present on the right hand side (RHS) of constraints. The solution is approached by decomposing the mp-MILP into two subproblems and then iterating between them. The first subproblem is obtained by fixing integer variables, resulting in a multiparametric linear programming (mp-LP) problem, whereas the second subproblem is formulated as a mixed integer linear programming (MILP) problem by relaxing the parameters as variables.     

Planning for optimal expansion of leased line communication networks

We report a new heuristic algorithm useful for developing least-cost expansion plans for leased telecommunications networks in which there is a hierarchy of possible transmission facilities. The problem combines network topology design and capacity expansion problems. Implemented on a PC, the algorithm has successfully developed topology growth plans for twenty periods on networks with up to 31 nodes.     

A simulated annealing algorithm for transient optimization in gas networks

In this paper we present a simulated annealing approach for the gas network optimization problem. A gas network consists of a set of pipes to transport the gas from the sources to the sinks whereby gas pressure gets lost due to friction. Further on there are compressors, which increase gas pressure, and valves. The aim is to minimize fuel gas consumption of the compressors whereas demands of consumers have to be satisfied. The problem of transient (time-dependent) optimization of gas networks results in a highly complex mixed integer nonlinear program. We relax the equations describing the gas dynamic in pipes by adding these constraints combined with appropriate penalty factors to the objective function. A suitable neighborhood structure is developed for the relaxed problem where time steps as well as pressure and flow of the gas are decoupled. Our approach convinces with flexibility and very good computational results.     

A Mixed Integer Formulation for Multiple-Route Transit Network Design

We consider the design of multiple transit lines in a network and present a mixed integer formulation for this multiple-route transit network design problem (MRTNDP). With the introduction of node labels, the formulation can exploit the route structure and hence attains efficiency in obtaining a cost minimizing transit network design. This revised version was published online in July 2006 with corrections to the Cover Date.     

Facility location models for planning a transatlantic communications network

This paper presents two facility location models for the problem of determining how to optimally serve the requirements for communication circuits between the United States and various European and Middle Eastern countries. Given a projection of future requirements, the problem is to plan for the economic growth of a communications network to satisfy these requirements. Both satellite and submarine cable facilities may be used. The objective is to find an optimal placement of cables (type, location, and timing) and the routing of individual circuits between demand points (over both satellites and cables) such that the total discounted cost over a T-period horizon is minimized. This problem is cast as a multiperiod, capacitated facility location problem. Two mathematical models differing in their provisions for network reliability are presented. Solution approaches are outlined and compared by means of computational experience. Use of the models both in planning the growth of the network and in the economic evaluation of different cable technologies is also discussed.     

基于城乡物流一体化的连锁经营配送网络优化研究

基于城乡物流一体化的目标设定和相应基础设施平台的支持,提出连锁经营配送网络的建设模式,依据对当前连锁经营网络发展的重点工作的分析,建立了关于配送中心和农产品收购中心选择的网络优化模型.并引入算例说明模型的可行性和适用性.