对带有盒约束的二次整数规划的一种线性化方法

本文主要讨论了二次整数规划问题的线性化方法.在目标函数为二次函数的情况下,我们讨论了带有二次约束的整数规划问题的线性化方法,并将文献中对二次0-1问题的研究拓展为对带有盒约束的二次整数规划问题的研究.最终将带有盒约束的二次整数规划问题转化为线性混合本文主要讨论了二次整数规划问题的线性化方法.在目标函数为二次函数的情况下,我们讨论了带有二次约束的整数规划问题的线性化方法,并将文献中对二次0-1问题的研究拓展为对带有盒约束的二次整数规划问题的研究.最终将带有盒约束的二次整数规划问题转化为线性混合0-1整数规划问题,然后利用Ilog-cplex或Excel软件中的规划求解工具进行求解,从而解决原二次整数规划.     

考虑协同信息的人员与岗位双边匹配决策方法

针对考虑协同信息的人员与岗位双边匹配问题,提出一种决策分析方法。首先,给出了考虑协同信息的人员与岗位双边匹配问题描述;其次,依据人员和岗位给出的多指标评价信息,计算了人员对岗位的满意度、岗位对人员的个体技能满意度及人员之间的工作协同度;在此基础上,建立了以人员对岗位满意度最大、岗位对人员个体技能满意度最大和人员之间协同度最大为目标的多目标优化模型,该模型是一个具有多目标的0-1型二次整数规划问题,也是一个NP-hard问题,为了求解该多目标优化模型,设计了一个多目标离散差分进化算法;最后,通过一个实例验证了所提方法的可行性和有效性。     

一类特殊二维0-1规划的广义指派模型求解

二维0-1整数规划模型应用广泛,对广义指派问题的研究,解决了一些二维0-1整数规划问题.但有些实际问题具有特殊上限约束,目前还没有对应的方法.针对该实际情形,本文建立了相应的数学模型,利用对指派模型的推广,求得问题最优解,从理论上解决了这一类特殊约束二维0-1整数规划的最优解求取问题.并通过算例说明了方法的使用.     

模糊环境下动态供应商选择的混合整数非线性规划模型

基于供应商选择问题的动态性和模糊性,考虑在每个周期内生产商的需求能力及供应商的供应能力为模糊变量,本文将一个多阶段多商品多渠道的供应商选择问题视为一个0-1混合整数模糊动态非线性规划问题,目标函数为总成本最小化。然后建立了0-1混合整数模糊动态非线性规划模型。为了求解该模型,通过可信性理论把模型中模糊机会约束清晰化,将该模型转化为一个确定型的0-1混合整数动态非线性规划模型。最后给出了一个数值算例验证了模型的可行性。     

整数规划新进展

整数规划是对全部或部分决策变量为整数的最优化问题的模型、算法及应用等的研究, 是运筹学和管理科学中应用最广泛的优化模型之一. 首先简要回顾整数规划的历史和发展进程, 概述线性和非线性整数规划的一些经典方法. 然后着重讨论整数规划若干新进展, 包括0-1二次规划的半定规划~(SDP)~松弛和随机化方法, 带半连续变量和稀疏约束的优化问题的整数规划模型和方法, 以及0-1二次规划的协正锥规划表示和协正锥的层级半定规划~(SDP)~逼近. 最后, 对整数规划未来研究方向进行展望并对一些公开问题进行讨论.     

考虑占位决策的围堵嫌犯模型

研究了2011年中国大学生数学建模竞赛B题的突发事件中交巡警对在逃嫌犯的围堵问题。不同于对该问题的以往的研究,本文考虑了交巡警在包围圈中可以占据某些路口,使得嫌犯不能通过这些被交巡警占据的路口,从而为形成包围圈的交巡警赢得更多时间。利用两篇相关文献的关于点截集判断的结论和考虑占位决策的建模方法,以不同的目标函数建立了考虑占位决策的围堵嫌犯问题的三个混合0-1非线性整数规划模型。通过选取部分线性约束和目标函数一起组合成混合0-1线性整数规划模型,设计了基于混合0-1线性整数规划方法的算法,并给出了算例。     

N车探险问题的一种ε-近似度的近似算法

本文探讨了一类N车探险问题的近似算法,首先通过建模将N车问题转变为一个等价的非线性0-1混合整数规划问题,进而将该非线性0-1混合整数规划问题转化为一个一般的带约束非线性规划问题,并用罚函数的方法将得到的带约束非线性规划问题化为相应的无约束问题.我们证明了可通过求解该无约束非线性规划问题得到原N车问题的ε-近似度的近似解,并设计了-个收敛速度为二阶的迭代箅法,文章最后给出算法实例.     

一类混合0-1非凸二次约束二次规划问题的近似算法

研究一类混合0-1非凸二次约束二次规划问题的近似算法.该问题是在M个非凸二次约束与一个基数约束下,求解一个n维向量的极小范数,变量包含M个0-1变量与一个n维连续向量.该问题是NP-难的.在求解其半正定规划(SDP)松弛问题的基础上,提出了一种随机舍入算法,能够得到原始的问题的一个可行解.数值仿真实验结果表明该方法是十分有效的.     

考虑协同效应的突发事件救援人员分组方法

针对突发事件的应急救援人员分组问题,提出了一种考虑人员间协同效应的应急救援人员分组方法。首先,对突发事件应急救援人员分组问题进行了描述。然后,基于系统协同理论的思想,提出了救援小组的协同度模型,定量化的度量救援人员间的协同效应。进一步地,综合考虑救援人员的基础效能与协同效应,基于协同度模型给出了救援人员完成不同任务的实际效能的表达式。在此基础上,以最大化各救援小组的实际效能为目标,构建了突发事件应急救援人员分组的优化模型,并给出了将这一多目标0-1二次规划模型转换为单目标0-1线性规划模型的方法,进而可求解并确定救援人员的最优分组方案。最后,通过一个实例分析说明了本文所提出方法的可行性和有效性。     

一个解非线性0-1整数规划问题基于罚函数的混合粒子群优化算法

利用罚函数思想把非线性0-1整数规划问题转化为无约束最优化问题,然后把粒子群优化和罚函数方法结合构造出一个基于罚函数的混合粒子群优化算法,数值结果表明所提出的算法是有效的.     

Parametric global optimisation for bilevel programming

We propose a global optimisation approach for the solution of various classes of bilevel programming problems (BLPP) based on recently developed parametric programming algorithms. We first describe how we can recast and solve the inner (follower’s) problem of the bilevel formulation as a multi-parametric programming problem, with parameters being the (unknown) variables of the outer (leader’s) problem. By inserting the obtained rational reaction sets in the upper level problem the overall problem is transformed into a set of independent quadratic, linear or mixed integer linear programming problems, which can be solved to global optimality. In particular, we solve bilevel quadratic and bilevel mixed integer linear problems, with or without right-hand-side uncertainty. A number of examples are presented to illustrate the steps and details of the proposed global optimisation strategy.     

Analysis of collaborative savings and cost allocation techniques for the cooperative carrier facility location problem

Transport companies may cooperate to increase their efficiency levels by, for example, the exchange of orders or vehicle capacity. In this paper a new approach to horizontal carrier collaboration is presented: the sharing of distribution centres (DCs) with partnering organisations. This problem can be classified as a cooperative facility location problem and formulated as an innovative mixed integer linear programme. To ensure cooperation sustainability, collaborative costs need to be allocated fairly to the different participants. To analyse the benefits of cooperative facility location and the effects of different cost allocation techniques, numerical experiments based on experimental design are carried out on a UK case study. Sharing DCs may lead to significant cost savings up to 21.6%. In contrast to the case of sharing orders or vehicles, there are diseconomies of scale in terms of the number of partners and more collaborative benefit can be expected when partners are unequal in size. Moreover, results indicate that horizontal collaboration at the level of DCs works well with a limited number of partners and can be based on intuitively appealing cost sharing techniques, which may reduce alliance complexity and enforce the strength of mutual partner relationships.     

Balancing of agricultural census data by using discrete optimization

In the case of large-scale surveys, such as a Census, data may contain errors or missing values. An automatic error correction procedure is therefore needed. We focus on the problem of restoring the consistency of agricultural data concerning cultivation areas and number of livestock, and we propose here an approach to this balancing problem based on optimization. Possible alternative models, either linear, quadratic or mixed integer, are presented. The mixed integer linear one has been preferred and used for the treatment of possibly unbalanced data records. Results on real-world Agricultural Census data show the effectiveness of the proposed approach.     

求解中大规模复杂凸二次整数规划问题的新型分枝定界算法

针对现有分枝定界算法在求解高维复杂二次整数规划问题时所存在的诸多不足，本文通过充分挖掘二次整数规划问题的结构特性来设计选择分枝变量与分枝方向的新方法，并将HNF算法与原问题松弛问题的求解相结合来寻求较好的初始整数可行解，由此导出可用于有效求解中大规模复杂二次整数规划问题的改进型分枝定界算法．数值试验结果表明所给算法大大改进了已有相关的分枝定界算法，并具有较好的稳定性与广泛的适用性．     

A continuous DC programming approach to the strategic supply chain design problem from qualified partner set

We present a new continuous approach based on the DC (difference of convex functions) programming and DC algorithms (DCA) to the problem of supply chain design at the strategic level when production of a new market opportunity has to be launched among a set of qualified partners. A well known formulation of this problem is the mixed integer linear program. In this paper, we reformulate this problem as a DC program by using an exact penalty technique. The proposed algorithm is a combination of DCA and Branch and Bound scheme. It works in a continuous domain but provides mixed integer solutions. Numerical simulations on many empirical data sets show the efficiency of our approach with respect to the standard Branch and Bound algorithm.     

A new variable reduction technique for convex integer quadratic programs

Convex integer quadratic programming involves minimization of a convex quadratic objective function with affine constraints and is a well-known NP-hard problem with a wide range of applications. We proposed a new variable reduction technique for convex integer quadratic programs (IQP). Based on the optimal values to the continuous relaxation of IQP and a feasible solution to IQP, the proposed technique can be applied to fix some decision variables of an IQP simultaneously at zero without sacrificing optimality. Using this technique, computational effort needed to solve IQP can be greatly reduced. Since a general convex bounded IQP (BIQP) can be transformed to a convex IQP, the proposed technique is also applicable for the convex BIQP. We report a computational study to demonstrate the efficacy of the proposed technique in solving quadratic knapsack problems.     

A fractional partial differential equation based multiscale denoising model for texture image

Traditional integer‐order partial differential equation based image denoising approach can easily lead edge and complex texture detail blur, thus its denoising effect for texture image is always not well. To solve the problem, we propose to implement a fractional partial differential equation (FPDE) based denoising model for texture image by applying a novel mathematical method—fractional calculus to image processing from the view of system evolution. Previous studies show that fractional calculus has some unique properties that it can nonlinearly enhance complex texture detail in digital image processing, which is obvious different with integer‐order differential calculus. The goal of the modeling is to overcome the problems of the existed denoising approaches by utilizing the aforementioned properties of fractional differential calculus. Using classic definition and property of fractional differential calculus, we extend integer‐order steepest descent approach to fractional field to implement fractional steepest descent approach. Then, based on the earlier fractional formulas, a FPDE based multiscale denoising model for texture image is proposed and further analyze optimal parameters value for FPDE based denoising model. The experimental results prove that the ability for preserving high‐frequency edge and complex texture information of the proposed fractional denoising model are obviously superior to traditional integral based algorithms, as for texture detail rich images. Copyright © 2013 John Wiley & Sons, Ltd.     

Two-stage quadratic integer programs with stochastic right-hand sides

We consider two-stage quadratic integer programs with stochastic right-hand sides, and present an equivalent reformulation using value functions. We propose a two-phase solution approach. The first phase constructs value functions of quadratic integer programs in both stages. The second phase solves the reformulation using a global branch-and-bound algorithm or a level-set approach. We derive some basic properties of value functions of quadratic integer programs and utilize them in our algorithms. We show that our approach can solve instances whose extensive forms are hundreds of orders of magnitude larger than the largest quadratic integer programming instances solved in the literature.