有时间窗的非满载车辆调度问题的遗传算法

有时间窗的车辆调度问题是一个典型的ＮＰ－难题,传统求解方法往往不能令人满意,本文将货运量约束和时间窗约束转化为目标约束,设计了基于自然数编码的可同时处理软、硬时间窗约束的遗传算法,实验分析获得了较好的结果。     

Primary Structural and Quantitative Analysis of Infeasible Solution to Job shop Scheduling Problem

1　IntroductionTheJobShopSchedulingProblemisawell-knownNP-hardproblem,whichattractslotsofmathematiciansallovertheworldspendingmuchtimeandenergyinthisfield.Uptonowtherearemanyefficientheuristicalgorithms,whichhadalreadybeendeveloped,buttheinfeasiblesolutioncertainlypossessesthemajorityofsearchspacewhichhasinfluencedtheefficiencyofthesealgorithms.Atthemoment,noonehasbeenfoundtobededicatingtothequantitativeanalysisoftheinfeasiblesolutionproblem.InthispaperthestructureofinfeasiblesolutiontoJSS…     

非满载车辆调度问题的遗传算法

非满载车辆调度问题是车辆调度问题中的一个基本问题,由于它是一个典型的NP难题,传统方法的求解结果往往不能令人满意。本文采用最大保留交叉、交叉率和变异率自适应变换等技术,设计了基于自然数编码的遗传算法,用于求解非满载车辆调度问题,在实验分析中获得了较好的结果。     

基于凸情形下在线设备更新问题的竞争分析

市场以在线的方式给出新设备,决策者必须决定是否更新现有的设备,并确定何时更新？即在已知现在和过去的设备信息和订单信息而对未来信息一无所知情况下,决策如何更新设备完成陆续达到的订单需求.优化目标是使设备更新投资成本与设备运行成本总和最小.首先讨论了离线设备更新问题, 给出了两种算法并分析了算法复杂度.其后, 讨论了凸情形下在线设备更新问题, 给出了临界值策略,得出了竞争比为6, 证明该策略要优于原有的策略.     

An Exact Logarithmic-exponential Multiplier Penalty Function

In this paper, we give a solving approach based on a logarithmic-exponential multiplier penalty function for the constrained minimization problem. It is proved exact in the sense that the global optimizers of a nonlinear problem are precisely the global optimizers of the logarithmic-exponential multiplier penalty problem.     

基于递阶遗传算法的一类多旅行商问题优化

针对最小化单个旅行商路程的多旅行商问题,提出了一种递阶遗传算法和矩阵解码方法。该算法根据问题的特点,采用一种递阶编码方案,此编码与多旅行商问题一一对应。用递阶遗传算法优化多旅行商问题不需设计专门的遗传算子,操作简单,并且解码方法适于求解距离对称和距离非对称的多旅行商问题。计算结果表明,递阶遗传算法是有效的,能适用于优化多旅行商问题。     

Closed circle DNA algorithm of change positive-weighted Hamilton circuit problem

Chain length of closed circle DNA is equal. The same closed circle DNA's position corresponds to different recognition sequence, and the same recognition sequence corresponds to different foreign DNA segment, so closed circle DNA computing model is generalized. For change positive-weighted Hamilton circuit problem, closed circle DNA algorithm is put forward. First, three groups of DNA encoding are encoded for all arcs, and deck groups are designed for all vertices. All possible solutions axe composed. Then, the feasible solutions axe filtered out by using group detect experiment, and the optimization solutions are obtained by using group insert experiment and electrophoresis experiment. Finally, all optimization solutions are found by using detect experiment. Complexity of algorithm is concluded and validity of DNA algorithm is explained by an example. Three dominances of the closed circle DNA algorithm are analyzed, and characteristics and dominances of group delete experiment axe discussed.     

A low order nonconforming anisotropic finite element approximation to parabolic problem

A low order nonconforming finite element is applied to the parabolic problem with anisotropic meshes. Both the semidiscrete and fully discrete forms are studied. Some superclose properties and superconvergence are obtained through some novel approaches and techniques. This research was supported by the National Natural Science Foundation of China under Grant No. 10671184.     

需求不确定性对最小化成本和最大化利润报童问题的影响

运用应用概率中的随机占优和可变序研究需求不确定性对两类报童问题的影响,一类是经典的最小化成本报童问题,另一类是带有二次订货策略的最大化利润报童问题. 得到对应于两类报童问题的最优成本（最优利润）关于缺货惩罚费用（二次订货费用）的单调性,并从最优化和随机比较两个方面分析两类模型的等价性. 针对最大化利润报童问题,给出在分散序意义下比较系统最优利润的充分条件,并证明当二次订货费用小于或等于零售价格时,随机大需求导致较高的最优利润,但当二次订货费用大于零售价格时此结论不一定成立. 证明对任意二次订货费用,在二阶随机占优意义下系统最优利润随需求可变性增加而减小. 进一步,证明存在一类需求分布,当需求均值相等且二次订货费用大于某一固定值时,系统最优利润随需求可变性的增加而增加. 对最小化成本报童问题给出类似的结果. 数值例子验证了得到的研究结果.     

求解双层CARP优化问题的知识型遗传算法

双层CARP优化问题首先考虑物流系统的宏观配置问题,然后考虑相关服务的完成问题. 提出了一种求解双层CARP优化问题的知识型遗传算法：采用两种扩展启发式方法来辅助生成初始种群;基于算子绩效知识为每次选择、交叉和变异操作选择合适的操作算子;基于弧段顺序知识为每次交叉和变异操作选择合适的断点位置;采用局部替换程序不断向当前种群中注入新个体. 实验结果表明,知识型遗传算法在优化性能方面优于其他几种方法.