含有批处理机的三机流水作业加工总长问题在某些情形下的强NP困难性

本文研究含有批处理机的三台机器流水作业加工总长问题在某些情形下的计算复杂性。在批处理机上同时加工的工件组成一个工件批，一个工件批的所有工件同时开始、同时结束。当批处理机的容量有限时，我们证明了下列情形为强NP困难的：第一台机器是批处理机、其余两台机器是单机；第二台机器是单机、其余两台机器是批处理机；第三台机器是批处理机、其余两台机器是单机。     

同型机和两台批处理机组成三阶段流水作业的最小加工全程问题

讨论一类三阶段流水作业的问题,第一阶段由m台同型机组成,第二阶段和第三阶段分别为1台批处理机,目标函数为最小加工全程.在同型机和两台批处理机上工件的加工时间分别相同情况下,给出了一般情况和几类特殊情况的算法.     

三机流水作业问题若干特殊情形的NP困难性

本文研究以加工总为目标函数的三台机器流水作业问题的特殊情形的计算复杂性,证明了下列情形为ＮＰ困难的：所有工作在第二台机器上有相同的加工时间;所有工作在第一和第三台机器上有相册的加工时间;每个工件至少有一个零工序;每个工件有一个丢失的工序。     

极小化总完工时间的同时加工排序

讨论了并行工件同时加工排序问题,即n个同时到达的工件在m台批处理机上排序的问题.批处理机一次最多能加工B个工件.每批的加工时间等于该批中所含工件的加工时间的最大者.主要考虑B n的特殊情况,即每批可包含任意多个工件,目标函数是极小化总完工时间.首先对同型批处理机的情况给出了动态规划算法,算法的运行时间为O(m nm+1),并进一步将结论推广到同类批处理机的情况.     

工件具有任意尺寸的混合分批平行机排序问题的近似算法

本文考虑了工件具有任意尺寸且机器有容量限制的混合分批平行机排序问题。在该问题中, 一个待加工的工件集需在多台平行批处理机上进行加工。每个工件有它的加工时间和尺寸, 每台机器可以同时处理多个工件, 称为一个批, 只要这些工件尺寸之和不超过其容量; 一个批的加工时间等于该批中工件的最大加工时间和总加工时间的加权和; 目标函数是极小化最大完工时间。该问题包含一维装箱问题为其特殊情形, 为强NP-困难的。对此给出了一个$\left( {2 + 2\alpha+\alpha^{2}}\right)$-近似算法, 其中$\alpha$为给定的权重参数, 满足$0\leq\alpha\leq 1$。     

工件具有任意尺寸的混合分批平行机排序问题的近似算法

本文考虑了工件具有任意尺寸且机器有容量限制的混合分批平行机排序问题。在该问题中, 一个待加工的工件集需在多台平行批处理机上进行加工。每个工件有它的加工时间和尺寸, 每台机器可以同时处理多个工件, 称为一个批, 只要这些工件尺寸之和不超过其容量; 一个批的加工时间等于该批中工件的最大加工时间和总加工时间的加权和; 目标函数是极小化最大完工时间。该问题包含一维装箱问题为其特殊情形, 为强NP-困难的。对此给出了一个$\left( {2 + 2\alpha+\alpha^{2}}\right)$-近似算法, 其中$\alpha$为给定的权重参数, 满足考虑了不同于Goldfarb和Iyengar （2003）的因子模型,通过横截面回归分析以及Fama-MacBeth估计构造了关于资产的平均收益向量和协方差矩阵的不确定性集合（置信区域）。基于这些不确定性集合以及Markowitz“均值-方差模型”的鲁棒投资组合问题,提出了多个鲁棒投资组合问题,并对应的推导出其等价的半正定规划形式,使得问题可以在多项式时间内求解。     

带运输时间和自动机的法流水作业排序问题的复杂性

研究目标函数为使最大完工时间达到最小的三台机器情况下的流水作业排序问题,同一工件在某台机器上完工后和在下一台机器上开始加工这段时间内,存在称为运输时间的时间间隔,所有的运输工作均由自动机来完成,自动机在同一时间内最多运输一个工件,文章研究该问题及其特殊情况下的复杂性.     

带运输时间和自动机的流水作业排序问题的复杂性

研究目标函数为使最大完工时间达到最小的三台机器情况下的流水作业排序问题, 同一工件在某台机器上完工后和在下一台机器上开始加工这段时间内, 存在称为运输时间的时间间隔, 所有的运输工作均由自动机来完成, 自动机在同一时间内最多运输一个工件, 文章研究该问题及其特殊情况下的复杂性.     

有使用限制的二台机器流水作业问题

本文研究了机器有使用限制的二台机器流水作业排序问题,目标为最小化最大完工时间,工件加工可以被机器的不可用时间段中断。我们讨论了两台机器上均有使用限制离线问题的可近似情形,并给出了性能比为3/2的近似算法。同时我们还考虑了在第二台机器上存在一个不可用时间段情况下的半在线问题,给出了一个竞争比为3/2的半在线算法。     

基于退化效应的两台机器流水作业可拒绝排序

考虑了工件具有退化效应的两台机器流水作业可拒绝排序问题,其中工件的加工时间是其开工时间的简单线性增加函数.每个工件或者被接收,依次在两台流水作业机器上被加工,或者被拒绝但需要支付一个确定的费用.考虑的目标是被接收工件的最大完工时间加上被拒绝工件的总拒绝费用之和.证明了问题是NP-难的,并提出了一个动态规划算法.最后对一种特殊情况设计了多项式时间最优算法.     

A permutation flow-shop scheduling problem with convex models of operation processing times

The paper is an extension of the classical permutation flow-shop scheduling problem to the case where some of the job operation processing times are convex decreasing functions of the amounts of resources (e.g., financial outlay, energy, raw material) allocated to the operations (or machines on which they are performed). Some precedence constraints among the jobs are given. For this extended permutation flow-shop problem, the objective is to find a processing order of the jobs (which will be the same on each machine) and an allocation of a constrained resource so as to minimize the duration required to complete all jobs (i.e., the makespan). A computational complexity analysis of the problem shows that the problem is NP-hard. An analysis of the structure of the optimal solutions provides some elimination properties, which are exploited in a branch-and-bound solution scheme. Three approximate algorithms, together with the results of some computational experiments conducted to test the effectiveness of the algorithms, are also presented. This revised version was published online in June 2006 with corrections to the Cover Date.     

Scheduling alternative operations in two-machine flow-shops

Most of the previous studies on scheduling problems assume that each machine is used exclusively for one operation although it has, in practice, potential to carry out some others. This paper studies two-machine flow-shop scheduling problems in which either or both machines are versatile so that alternative operations are possible. Branch-and-bound algorithms are developed to minimize the makespan of jobs for these problems and computational experiments are conducted to illustrate the effectiveness of these algorithms.     

Realistic two-stage flowshop batch scheduling problems with transportation capacity and times

This paper investigates single-batch and batch-single flow shop scheduling problem taking transportation among machines into account. Both transportation capacity and transportation times are explicitly considered. While the single processing machine processes one job at a time, the batch processing machine processes a batch of jobs simultaneously. The batch processing time is the longest processing times of jobs assigned to that batch.Each problem is formulated as a mixed integer programming model to find optimal makespan. Lower bounds and heuristic algorithms are proposed and computational experiments are carried out to verify their effectiveness.     

Minimizing makespan and total completion time for parallel batch processing machines with non-identical job sizes

This paper considers the scheduling problem of parallel batch processing machines with non-identical job sizes. The jobs are processed in batches and the machines have the same capacity. The models of minimizing makespan and total completion time are given using mixed integer programming method and the computational complexity is analyzed. The bound on the number of feasible solutions is given and the properties of the optimal solutions are presented. Then a polynomial time algorithm is proposed and the worst case ratios for minimizing total completion time and makespan is proved to be 2 and (8/3–2/3 m) respectively. To test the proposed algorithm, we generate different levels of random instances. The computational results demonstrate the effectiveness of the algorithm for minimizing the two objectives.     

Flow-shop scheduling with a learning effect

The paper is devoted to some flow-shop scheduling problems with a learning effect. The objective is to minimize one of the two regular performance criteria, namely, makespan and total flowtime. A heuristic algorithm with worst-case bound m for each criteria is given, where m is the number of machines. Furthermore, a polynomial algorithm is proposed for both of the special cases: identical processing time on each machine and an increasing series of dominating machines. An example is also constructed to show that the classical Johnson's rule is not the optimal solution for the two-machine flow-shop scheduling to minimize makespan with a learning effect. Some extensions of the problem are also shown.     

Complexity Results for Flow-Shop and Open-Shop Scheduling Problems with Transportation Delays

We consider shop problems with transportation delays where not only the jobs on the machines have to be scheduled, but also transportation of the jobs between the machines has to be taken into account. Jobs consisting of a given number of operations have to be processed on machines in such a way that each machine processes at most one operation at a time and a job is not processed by more than one machine simultaneously. Transportation delays occur if a job changes from one machine to another. The objective is to find a feasible schedule which minimizes some objective function. A survey of known complexity results for flow-shop and open-shop environments is given and some new complexity results are derived.     

A variable neighbourhood search for hybrid flow-shop scheduling problem with rework and set-up times

This paper deals with hybrid flow-shop scheduling problem with rework. In this problem, jobs are inspected at the last stage, and poorly processed jobs were returned and processed again. Thus, a job may visit a stage more than once, and we have a hybrid flow-shop with re-entrant flow. This kind of a shop may occur in many industries, such as final inspection system in automotive manufacturing. The criterion is to minimize the makespan of the system. We developed a 0–1 mixed-integer program of the problem. Since the hybrid flow-shop scheduling problem is NP-hard, an algorithm for finding an optimal solution in polynomial time does not exist. So we generalized some heuristic methods based on several basic dispatching rules and proposed a variable neighbourhood search (VNS) for the problem with sequence-dependent set-up times and unrelated parallel machines. The computational experiments show that VNS provides better solutions than heuristic methods.     

A travelling salesman approach to solve the F/no-idle/Cmax problem

This paper investigates the F/no-idle/C_max problem, where machines work continuously without idle time intervals. The idle characteristic is a very strong constraint and it affects seriously the value of C_max criterion. We treat here only the permutation flow-shop configuration for machine no-idle problems with the objective to minimise the makespan. Based on the idea that this problem can be modelled as a travelling salesman problem, an adaptation of the well-known nearest insertion rule is proposed to solve it. A computational study shows the result quality.