求解带组换装时间单机调度问题的禁忌搜索算法

以包头某钢铁线材企业生产实际调度问题为背景,研究了一类带组换装时间的单机调度问题.由于该问题是NP难的,本文提出了一类适合该问题的禁忌搜索算法.此外,本文将问题性质引入了禁忌搜索算法以进一步提高算法寻优性能,降低算法运行时间.本文提出的算法在随机问题和实际问题上均进行了测试,实验结果表明,本文提出的算法能在不到10秒的时间内获得实际问题的一个近似最优解.     

布谷鸟算法求解置换流水车间调度问题

置换流水车间调度问题是典型的生产调度问题,当其规模大于3时已被证明是Np-hard问题.布谷鸟算法是新的群体智能算法,该算法选用参数少且有较强的全局寻优能力.采用最大位置法编码,以最小化最大完工时间为目标,为验证该算法在不同参数支配下的寻优效果,分别在不同影响因素下对Car8问题独立运行100次.为验证算法的优化性能,将Car1-Car8问题的寻优结果与猫群算法寻优结果相比较.结果均证明该算法求解离散调度问题的优越的优化性能.     

改进伪并行遗传算法求解作业车间调度问题

针对遗传算法在求解极复杂优化问题中出现的过早收敛、执行效率差的缺点,提出了一种改进的伪并行遗传算法.该算法将并行进化与串行搜索相结合,提高了算法的收敛速度.同时该算法通过种群因子控制伪并行算法中的各子种群的规模,不仅保证了搜索过程中勘探和开采的平衡,克服过早收敛,而且减少了计算的复杂性,特别是在处理复杂优化问题上具有较高的性能.实验结果证明了该算法的有效性.     

二阶锥权互补问题的非精确非内点连续化算法

基于二阶锥权互补函数,将二阶锥权互补问题转化为一个方程组,运用非精确非内点连续化算法求解该方程组.该算法能以任意点作为初始点,且每次迭代时至多求解一个方程组.为节省算法求解方程组时的计算时间和内存,将非精确牛顿法引入到算法中.在适当假设下,证明了该算法是全局与局部二阶收敛的.最后数值实验表明了算法的良好性能.     

考虑帕累托最优解的多目标优化进化算法

大多数现有的进化算法在处理多目标优化问题(multi-objective optimization problem,MOP)时会遇到Pareto最优解稀疏的困难,特别是当决策变量的数目很大时,如旨在从大量候选特征中找出小部分特征的特征选择.为此,提出了一种求解大规模稀疏MOP的进化算法.算法考虑Pareto最优解的稀疏性,提出了一种新的种群初始化策略和遗传算子,以保证解的稀疏性.此外,还设计了一个测试套件来评估该算法在大规模稀疏MOP中的性能,实验结果和应用实例证明了该算法在处理大规模稀疏MOP问题上的优越性.     

基于模拟植物生长算法构造Steiner最优树问题研究

Steiner最优树问题是指对于给定区域内的点集,通过引入Steiner点集将区域中的点连接并保证连通的网络达到最小.该问题已成为经典的优化组合问题之一.提出一种基于模拟植物生长算法生成Steiner最优树的连通算法来实现网络连通.通过对实例的实验及结果分析,结果表明本算法不仅可获得最优解,精度和性能也有提高,明显优于其它方法.     

求解图像分割CV模型的BB算法

给出图像分割的一种新算法——BB算法.该方法的优点在于利用迭代过程中当前点和前一点的信息确定搜索步长,从而更有效地搜索最优解.为此,首先通过变分水平集方法将CV模型转化为最优化问题;其次,将BB算法引入该优化问题进行求解;然后,对BB算法进行收敛性分析,为该算法应用在CV模型中提供了理论依据;最后将该方法与已有的最速下降法、共轭梯度法的分割结果进行比较.结果表明,跟其他两种方法相比,BB算法在保证较好分割效果的前提下,提高了算法的速度和性能.     

带组约束可靠性网络最优化问题的精确算法

本文提出了一种求解带组约束串-并网络系统最优冗余问题的精确算法.该算法利用拉格朗日松驰和Dantzig-Wolfe分解法得到问题的上界,并结合动态规划求解子问题.算法采用一种有效的切割和剖分方法,以逐步缩小对偶间隙和保证收敛性.数值结果表明该算法对于求解带组约束可靠性最优化问题是很有效的.     

自对偶嵌入模型解拓展熵规划

本文把拓展熵规划转化为锥最优化问题,再对该锥最优化问题构造一个锥自对偶嵌入模型,证明了锥自对偶嵌入模型的障碍函数满足自协调性,这保证了用某些内点法求解时算法是多项式时间的.这种方法的另一个优点是不需要寻找初始可行解.     

一类带多重核元集在线装箱问题

本文讨论了一类在线变尺寸装箱问题,假定箱子的尺寸可以是不同的.箱子是在线到达的,仅当箱子到达后其尺寸才知道.给定一个带有核元的物品表及其上的核元关系图.我们的目标是要将表中元素装入到达的箱子中,保证任何箱子所装物品不互为核元,即所装物品对应的点所导出的子图是个空图,并使得所用的箱子总长最小.我们证明了该问题是NPHard的,并给出了基于图的点染色、图的团分解和基于背包问题的近似算法,给出了算法的时间复杂度和性能界.     

Machine scheduling with a maintenance interval and job delivery coordination

We investigate a scheduling problem with job delivery coordination in which the machine has a maintenance time interval. The goal is to minimize the makespan. In the problem, each job needs to be processed on the machine non-preemptively for a certain time, and then transported to a distribution center, by one vehicle with a limited physical capacity. We present a 2-approximation algorithm for the problem, and show that the performance ratio is tight.     

A branch and bound algorithm for hybrid flow shop scheduling problem with setup time and assembly operations

A hybrid flow shop scheduling problem (HFSP) with assembly operations is studied in this paper. In the considered problem, a number of products of the same kind are produced. Each product is assembled using a set of several parts. At first, the parts are produced in a hybrid flow shop and then they are assembled in an assembly stage to produce products. The considered objective is to minimize the completion time of all products (makespan). This problem has been proved strongly NP-hard, so in order to solve it, a hierarchical branch and bound algorithm is presented. Also, some lower and upper bounds are developed to increase the efficiency of the proposed algorithm. The numerical experiments are used to evaluate the performance of the proposed algorithm.     

Scheduling jobs on a single machine with release dates, delivery times and controllable processing times: worst-case analysis

The paper deals with the problem of scheduling jobs on a single machine, in which each job has a release date, a delivery time and a controllable processing time, having its own associated linearly varying cost. An approximation algorithm for minimizing the overall schedule cost is provided which has the performance guarantee of , where is the worst-case performance bound of a procedure used in the proposed algorithm for solving the pure sequencing problem. The best approximation procedure known has .     

超尺寸物品装箱问题及其算法

本文探讨一类新装箱问题-超尺寸物品装箱问题。针对实际解决该问题的两涉法，我们提出了一个评价效率更高的目标函数，证明了在此目标函数下两步法的渐近最坏比不小于2，并给出了渐近量坏比与拆分次数的关系。最后本文提出了一种不同于两步法的新在线算法MA，证明了在新目标函数下其渐近最坏比不超过7/4。     

Integrated service network design for a cross-docking supply chain network

This paper considers an integrated service network design problem for a given set of freight demands that is concerned with integration of locating cross-docking (CD) centers and allocating vehicles for the associated direct (transportation) services from origin node to a CD center or from a CD center to the destination node. For the vehicle allocation, direct services (sub-routes) should be determined for the given freight demands, and then the vehicle allocation has to be made in consideration of routing for the associated direct service fulfillment subject to vehicle capacity and service time restriction. The problem is modeled as a path-based formulation for which a tabu-search-based solution algorithm is proposed. To guarantee the performance of the proposed solution algorithm, strong valid inequalities are derived based on the polyhedral characteristics of the problem domain and an efficient separation heuristic is derived for identifying any violated valid inequalities. Computational experiments are performed to test the performance of the proposed solution algorithm and also that of a valid-inequality separation algorithm, which finds that the solution algorithm works quite well and the separation algorithm provides strengthened lower bounds. Its immediate application may be made to strategic (integrated) service network designs and to tactical service network planning for the CD network.     

Two-machine flowshop scheduling problems involving a batching machine with transportation or deterioration consideration

This paper considers two scheduling problems for a two-machine flowshop where a single machine is followed by a batching machine. The first problem is that there is a transporter to carry the jobs between machines. The second problem is that there are deteriorating jobs to be processed on the single machine. For the first problem with minimizing the makespan, we formulate it as a mixed integer programming model and then prove that it is strongly NP-hard. A heuristic algorithm is proposed for solving this problem and its worst case performance is analyzed. The computational experiments are carried out and the numerical results show that the heuristic algorithm is effective. For the second problem, we derive the optimal algorithms with polynomial time for minimizing the makespan, the total completion time and the maximum lateness, respectively.     

基于支持向量机的多类分类问题的一种新算法

在K-SVCR算法结构的基础上构造了新的模型.模型的特点是它的一阶最优化条件可以转化为一个线性互补问题,通过Lagrangian隐含数,可以将其进一步转化成一个强凸的无约束优化问题.利用共轭梯度技术对其进行求解,在有限步内得到分类超平面.最后在标准数据集进行了初步试验.试验结果显示了提出的算法在分类的精度和速度上都有明显提高.     

Part type selection problem in flexible manufacturing systems: tabu search algorithms

Production planning in flexible manufacturing systems is concerned with the organization of production in order to satisfy a given master production schedule. The planning problem typically gives rise to several hierarchical subproblems which are then solved sequentially or simultaneously. In this paper, we address one of the subproblems: the part type selection problem. The problem is to determine a subset of part types having production requirements for immediate and simultaneous processing over the upcoming period of the planning horizon, subject to the tool magazine and processing time limitation. Several versions of tabu search (TS) algorithm are proposed for solving the problem. A systematic computational test is conducted to test the performance of the TS algorithms. The best TS algorithm developed is compared to a simulated annealing algorithm.     

Bi-criteria single machine scheduling with a time-dependent learning effect and release times

This paper deals with a bi-criteria single machine scheduling problem with a time-dependent learning effect and release times. The objective is to minimize the weighted sum of the makespan and the total completion time. The problem is NP-hard, thus a mixed integer non-linear programming formulation is presented, and a set of dominance properties are developed. To solve the problem efficiently, a procedure is then proposed by incorporating the dominance properties with an ant colony optimization algorithm. In the proposed algorithm, artificial ants construct solutions as orders of jobs based on the heuristic information as well as pheromone trails. Then, the dominance properties are added to obtain better solutions. To evaluate the algorithm performance, computational experiments are conducted.     

改进的蝗虫优化算法在双目标应急物资中心选址问题中的应用

近年来世界各地频发灾情疫情等紧急事件,严重影响人民的生活物资保障。在这种情况下,急需建立应急物资中心来缓解燃眉之急。该类问题通常面临资源稀缺并且时间相对紧迫的处境,因此需要在短时间内获得合理的应急设施选址方案来提升服务的质量和效率。本文对应急物资中心选址问题展开研究,提出一种考虑后续运输成本以及有概率发生紧急事件而导致无法正常运送物资的双目标离散选址模型,并为此设计一种二进制多目标蝗虫优化算法。该算法采用模糊关联熵系数来引导迭代更新,同时为其添加外部档案,最优解选择机制和竞争决策机制来提升算法性能。多次数值实验表明该算法的计算效率和求解质量较高,可作为应急物资中心选址问题的一种可行且有效的算法。