光线寻优算法的寻优机理分析

Based on Fermat’s principle and the automatic optimization mechanism in the propagation process of light,an optimal searching algorithm named light ray optimization is presented,where the laws of refraction and reflection of light rays are integrated into searching process of optimization.In this algorithm,coordinate space is assumed to be the space that is full of media with different refractivities,then the space is divided by grids,and finally the searching path is assumed to be the propagation path of light rays.With the law of refraction,the search direction is deflected to the direction that makes the value of objective function decrease.With the law of reflection,the search direction is changed,which makes the search continue when it cannot keep going with refraction.Only the function values of objective problems are used and there is no artificial rule in light ray optimization,so it is simple and easy to realize.Theoretical analysis and the results of numerical experiments show that the algorithm is feasible and effective.     

整数线性规划投资组合模型的直接搜索算法求解

利用松弛最优邻近解临域整数点搜索法作过滤条件,建立求解整数规划的新方法——直接搜索算法,利用直接搜索算法并借助Matlab软件求解整数线性规划投资组合模型.数值结果表明了模型的建立与提出方法的有效性.     

社会经济管理系统和谐性模型的构建与分析

本文从非线性自然观的视野。引用与分析了社会经济系统功能模型与效应模型。构建了系统和谐状态模型与和谐状态可信度模型，形象地说明了企业系统的和谐既是一个随机不确定状态。又是企业和谐力量与不和谐力量相互抗争干涉的过程。依据协同学原理提出了企业系统和谐演进的机制，表明企业系统的和谐发展是子系统和谐协同的过程。即子系统竞争合作的过程。文中所构建的模型，从理论上清晰地说明了企业系统和谐有序运行的机理，为如何构建和谐企业。提供了建设性的思考。     

服务管理目标优化配置的Fuzzy-QFD线性规划模型构建与求解

由于服务管理的复杂性和模糊性,现有方法难以有效解决基于主观语言评价的服务质量改进问题。本文拓展了质量功能展开(QFD)方法在服务业中的应用,通过构建一个模糊线性规划模型,以求解最大化提高顾客需求综合满意度的企业能力优化配置问题。首先基于顾客感知-期望差距的模糊评估确定顾客需求、需求权重和边界约束等模型参数,接着运用模糊线性回归和非对称三角模糊数的隶属函数,将含有模糊变量的模糊线性规划问题转化为经典线性规划问题,进而求得不同模糊条件下的模型解。最后通过网购平台的实例验证了模型的有效性和可行性。     

改进的松鼠搜索算法求解手术时间不确定的手术病例分配问题

针对手术病例分配问题特点,本文结合医院实际运作情况,考虑手术时间的不确定性,通过引入三角模糊数,建立以最小化模糊运营成本为优化目标的手术病例分配问题模型,提出一种改进松鼠搜索算法用于该模型的求解。算法改进包括:设计了一种基于手术编号的单列编码方案以及对应的解码策略;根据问题特点嵌入了有效的启发式策略进一步提高种群质量;改进了松鼠搜索操作使其适用于该模型的求解;采用了多种局部搜索策略提高算法收敛速度及效率。仿真实验和对比分析表明,所提算法在求解手术时间不确定的手术病例分配问题中表现出较强的有效性和稳定性。     

Quickest search over Brownian channels

In this paper we resolve an open problem proposed by Lai, Vincent Poor, Xin, and Georgiadis [Quickest search over multiple sequences. IEEE Trans. Inf. Theory 57(8) (2011), pp. 5375–5386]. Consider a sequence of Brownian motions with unknown drift equal to one or zero, which may be observed one at a time. We give a procedure for finding, as quickly as possible, a process which is a Brownian motion with non-zero drift. This original quickest search problem, in which the filtration itself is dependent on the observation strategy, is reduced to a single filtration impulse control and optimal stopping problem, which is in turn reduced to an optimal stopping problem for a reflected diffusion, which can be explicitly solved.     

Controlling Type II Error While Constructing Triple Sampling Fixed Precision Confidence Intervals for the Normal Mean

The rationale and methodology for estimating a mean with a fixed width confidence interval through sampling in three stages are extended to cover the additional problem of testing hypotheses concerning shifts in the mean with controlled Type II error. The coverage probability and operating characteristic function of the confidence interval based on the integrated approach are derived and compared with those of the usual triple sampling confidence interval. The extended methodology leads to better coverage probability and uniformly better Type II error probabilities. Achieving the additional objective of controlling Type II error inevitably implies a two- to threefold increase in the required optimal sample size. Some suggestions for dealing with this apparent limitation are discussed from a practical viewpoint. It is recommended that an integrated approach to estimation and testing based on confidence intervals be incorporated in the design stage for credible inferences.     

Heuristic Techniques for Single Line Train Scheduling

Optimising a train schedule on a single line track is known to be NP-Hard with respect to the number of conflicts in the schedule. This makes it difficult to determine optimum solutions to real life problems in reasonable time and raises the need for good heuristic techniques. The heuristics applied and compared in this paper are a local search heuristic with an improved neighbourhood structure, genetic algorithms, tabu search and two hybrid algorithms. When no time constraints are enforced on solution time, the genetic and hybrid algorithms were within five percent of the optimal solution for at least ninety percent of the test problems.     

The computation of Buehler confidence limits

In medicine and industry, small sample size often arises owing to the high test cost. Then exact confidence inference is important. Buehler confidence limit is a kind of exact confidence limit for the function of parameters in a model. It can be always defined if the order in sample space is given. But the computing problem is often difficult, especially for the cases with high dimension parameter or with incomplete data. This paper presents an algorithm to compute the Buehler confidence limits by EM algorithm. This is the first-time usage of EM algorithm on Buehler confidence limits, but the algorithm is often used for maximum likelihood estimate in literatures. Three computation examples are given to illustrate the method.     

Optimal discrete search with imperfect specificity

A target is hidden in one of several possible locations, and the objective is to find the target as fast as possible. One common measure of effectiveness for the search process is the expected time of the search. This type of search optimization problem has been addressed and solved in the literature for the case where the searcher has imperfect sensitivity (possible false negative results), but perfect specificity (no false positive detections). In this paper, which is motivated by recent military and homeland security search situations, we extend the results to the case where the search is subject to false positive detections.     

Integrated scheduling and batch ordering for construction project

Multi-Mode Resource Constrained Project Scheduling Problem and material batch ordering for construction project are integrated to help project manager consider various trade-offs among several costs, such as renewable resources’ cost, material price, ordering cost, back-ordering cost, inventory holding cost and reward/penalty for early/late project completion. Therefore, we prove a mixed integer programming model and impel to calculate inventory holding cost and back order cost in objective function. Moreover, a hybrid algorithm combined adapted harmony search and genetic algorithm is proposed correspondingly. In order to inherit elitist solution and maintain population’s diversity simultaneously, we add a selection operator when the harmony memory is initialized and modify the replacement operator based on distance. Besides, genetic algorithm is adopted based on a ‘012’ coding scheme. Finally, algorithm and model performance is presented and several project instances are provided with different network structures and realizations to discuss the factors on total cost.     

基于遗传禁忌算法的双资源约束下并行生产线调度研究

并行生产线调度问题兼有并行机器和流程车间调度问题的特点,是一类新型的调度问题。在考虑遗传算法早熟收敛特性和禁忌搜索法自适应优点的基础上,将遗传算法和禁忌搜索法结合起来,提出了基于遗传算法和禁忌搜索算法的双资源并行作业车间的调度优化问题算法,即考虑到了产品的调度受到机器、工人等资源制约的影响,对算法中种群的构造,适应度计算,遗传操作等方面进行了研究,最后给出了实例仿真和结论。     

一类系数为梯形模糊数的整数规划

介绍了模糊数学和整数规划的背景、现状、以及发展趋势,并以模糊结构元理论定义了梯形模糊加权序,进一步证明了模糊整数规划模型的最优解等价于整数规划模型的最优解,再利用整数规划模型的最优解的求解方法求解模糊整数规划模型的最优解,最后,通过算例验证方法的可行性.     

The service allocation problem at the Gioia Tauro Maritime Terminal

The Service Allocation Problem (SAP) is a tactical problem arising in the yard management of a container transshipment terminal. The objective is the minimization of the container rehandling operations inside the yard. This study of the SAP was undertaken for the Gioia Tauro port which is located in Italy and is the main hub terminal for container traffic in the Mediterranean Sea. The SAP can be formulated as a Generalized Quadratic Assignment Problem (GQAP) with side constraints. Two mixed integer linear programming formulations are presented. The first one exploits characteristics of the yard layout at Gioia Tauro where the berth and the corresponding yard positions extend along a line. The second formulation is an adaptation of a linearization for the GQAP. In both cases only small instances can be solved optimally. An evolutionary heuristic was therefore developed. For small size instances the heuristic always yields optimal solutions. For larger sizes it is always better than a truncated branch-and-bound algorithm applied to the exact formulations.     

三维多箱异构货物装载优化及其可视化

针对七种现实约束的集装箱三维多箱异构货物装载优化问题,提出了一种基于 “块”和“空间”的启发式搜索算法。算法采用树搜索策略,根据可用空间,对每一次搜索的货物块进行评估,得到最佳的货物块,直到无可用空间或无可装载的货物为止。基于开放式标准测试数据的计算结果表明,该算法在时间效率和体积利用率上均优于已有的同类研究。并基于Net平台开发了一款3D装箱布局优化可视化软件,已在相关物流企业中得到推广应用,验证了算法的实用性。     

“应召”搜索问题的最优搜索路线

解决了确定性二次搜索（即“应召”搜索）问题的最优搜索路线。在搜索时间期望值最小、最远可能航程最短、最长可能时间最短三个准则下分别找出了相应的最优搜索路线,并从理论上严格证明了三者的统一性。这个结论在军事领域具有很重要的应用价值     

P-枢纽航线网络设计问题的一种启发式算法

针对无容量限制的多重分派枢纽中位问题(UMApHMP),提出了一种基于禁忌搜索和最短路算法的新的启发式算法。利用CAB基准数据对该算法进行了验证,计算结果表明所提算法具有较强寻优能力和较快的求解效率。