An interactive dynamic approach based on hybrid swarm optimization for solving multiobjective programming problem with fuzzy parameters

Real engineering design problems are generally characterized by the presence of many often conflicting and incommensurable objectives. Naturally, these objectives involve many parameters whose possible values may be assigned by the experts. The aim of this paper is to introduce a hybrid approach combining three optimization techniques, dynamic programming (DP), genetic algorithms and particle swarm optimization (PSO). Our approach integrates the merits of both DP and artificial optimization techniques and it has two characteristic features. Firstly, the proposed algorithm converts fuzzy multiobjective optimization problem to a sequence of a crisp nonlinear programming problems. Secondly, the proposed algorithm uses H-SOA for solving nonlinear programming problem. In which, any complex problem under certain structure can be solved and there is no need for the existence of some properties rather than traditional methods that need some features of the problem such as differentiability and continuity. Finally, with different degree of α we get different α-Pareto optimal solution of the problem. A numerical example is given to illustrate the results developed in this paper.     

网络最小覆盖流问题

网络流理论中最基本的模型是最大流及最小费用流问题. 为研 究堵塞现象, 文献中出现了最小饱和流问题, 但它是NP-难的. 研究类似的最小覆盖流问题, 即求一流, 使每一条弧的流量达到一定的额定量, 而流的值为最小. 主要结果是给出多项式时间算法, 并应用于最小饱和流问题.     

沿海港口集装箱空箱调运策略优化模型

我国沿海港口进出口箱分布非常不均衡,由此产生了集装箱空箱调运现象,合理的空箱调运策略能够有效地降低航运成本。本文研究了沿海港口间的空箱调运问题。在传统确定目的港策略的基础上,提出了一种新的空箱调运策略,不确定目的港策略。针对两种不同调运策略分别建立了以总调运费用最小为目标的规划模型。并以中国沿海港口空箱调运为例,运用遗传算法,在不同的空箱供需情况下,对两种调运策略费用进行了优化求解。结果表明,供需平衡模式下,固定目的港策略略有优势;在供需不平衡模式中,不确定目的港策略优势更加明显。此研究能够为港口间空箱调运提供辅助决策。     

应急物流中库存与运输集成决策模型研究

已有的研究表明,在物流管理中权衡库存与运输成本之间的关系,实现两者的集成决策,可改进系统的运作绩效。在给定的仓库布局条件下,针对应急物流的配送特点,构建了单周期物资的运输与库存集成决策的随机规划模型。考虑到模型求解的复杂性,首先通过对模型的分析,获得了最优解的性质和上界,然后设计了基于BP神经网络和遗传算法的混合智能算法。在算例分析部分,揭示了服务水平、运输、和库存成本在应急物流中之间的复杂关系,说明合理权衡三者之间的关系,可以提升应急物流的管理水平。     

基于权值编码的组合拍卖竞胜标确定启发式算法研究

针对较大规模组合拍卖竞胜标确定问题(WDP),提出了基于权值编码的竞胜标确定启发式算法.改进了算法编码机制并嵌入基于WDP本质特点的启发式搜索规则,极大地提高了算法进化能力和求解效率.模拟实验结果表明该算法能够在较短时间内求出WDP最优解或满意近似解,为较大规模网上组合拍卖竞胜标确定问题提供了切实可行的求解算法.     

交叉概率对改进遗传算法运算速度影响的测试与分析

在现有文献基础上,通过理论分析,提出了交叉概率应取1.通过四个测试函数的测试结果,表明交叉概率越大,运算速度越快,平均运行代数越少,验证了通过理论分析提出的交叉概率应取1的科学性和可行性.同时克服了交叉概率难以确定以及确定交叉概率时缺少理论依据的不足.     

变循环发动机模型的求解算法研究

采用部件法建立了变循环发动机的多维非线性隐式方程组模型,模型具有隐式性,因而求解过程复杂,收敛困难.针对上述问题,采用遗传算法和牛顿-拉夫逊法进行模型求解,提出了算法的有效性评价指标:初值敏感性、收敛性和稳定性.对两种算法进行有效性评价.针对发动机工作性能最优化问题,建立了多目标模型,用遗传算法进行求解,并分析了相关变量随马赫数变化的规律.结果可为变循环发动机模型求解算法的选择与设计提供参考.     

一种抗高阶旁路攻击的LED密码算法

LED密码算法是2011年提出的超轻量级密码算法,主要是为资源受限下物联网加密应用研发的.轻量级密码算法结构相对简单,更容易被旁路攻击成功.随机掩码是一种有效抗旁路攻击的方法,在深入LED密码算法结构研究的基础上,提出一种全随机掩码的LED密码算法CMLED.论述了CMLED算法的设计方法,从形式化方面给出了抗高阶旁路攻击选择掩码的原则.同时,对全随机掩码的CMLED与原始算法进行了硬件资源占用与加密效率对比,实验表明CMLED仍然可以高效地在智能卡上实现.     

A genetic algorithm for optimizing defective goods supply chain costs using JIT logistics and each-cycle lengths

The competitive environment of global markets has forced many manufacturers to select the most appropriate supply chain network (SCN) for reduction of total costs and wasted time. Cost reduction and selection of the appropriate length of each period are two important factors in the competitive market that are often not addressed comprehensively by researchers. In our study, we proposed genetic algorithms (GAs) for optimising a novel mathematical model of the defective goods supply chain network (DGSCN). In the proposed model, we assumed that all imperfect-quality products are not repairable, whereas those considered as scrap are directly sold to customers at a low price. The objective of the proposed model is to minimise the costs of production, distribution, holding and backorder. In addition to minimising the costs, the model can determine the economic production quantity (EPQ), the appropriate length of each cycle (ALOEC) and the quantities of defective products, scrap products and retailer shortages using Just-In-Time logistics (JIT-L). We used the GAs and a Cplex solver with probability parameters and various dimensions for validation of the studied model in real-life situations, and we compared the outputs to demonstrate the performance of the model. Additionally, to identify the appropriate length of each cycle (ALOEC), we needed to solve the model using exact parameters and same dimensions and prefer to use Lingo for this application.     

Optimal deterministic algorithms for some variants of Online Quota Traveling Salesman Problem

This paper is concerned with the Online Quota Traveling Salesman Problem. Depending on the symmetry of the metric and the requirement for the salesman to return to the origin, four variants are analyzed. We present optimal deterministic algorithms for each variant defined on a general space, a real line, or a half-line. As a byproduct, an improved lower bound for a variant of Online TSP on a half-line is also obtained.