总延误问题顺时安排法的性能比

给定一组工件的加工时间与工期，要求确定这些工件在一台机器上的加．工排列，使相应的总延误达到最小，这就是总延误问题．该问题在近年已被证明是NP困难的．由Wilkermn和Irwin（1971），林勋（1983）等所研究的顺时安排法能得到相邻交换意义下的局部解．在本文中，我们进一步证明该算法能得到前移邻域意义下的局部解，并确定了该算法的性能比．     

有分离调整和移走时间的两机器流水作业最大延误问题

在工件的调整时间和移走时间独立于加工时间的两机器流水作业问题中，同一工件的“调整”步及“移走”步在两台机器上可重叠进行，但“加工”步不能重叠，本以最大延误为目标函数讨论问题的解中工件排列应满足的条件，根据这些条件我们构作了两个近似算法。     

基于遗传算法的批调度问题

对把独立的、可同时达到的工件组批，并同时在单机上确定批内序和批间序的批调度问题进行了研究。给出了问题的数学模型，并构造了一个有效的遗传算法。实验结果表明是有效的。     

Bicriteria problems to minimize maximum tardiness and due date assignment cost in various scheduling environments

We study bicriteria problems of minimizing maximum tardiness and total due date assignment cost in various scheduling environments. We assume that each job can be assigned a different due date without any restriction, and that each due date assignment cost is a non-decreasing function of the quoted due date. We settle the complexity of most of the problems studied by either proving that they are NP-hard or finding a polynomial time solution for them. We also include approximation and non-approximability results for several parallel-machine problems.     

Single machine scheduling with family setups to minimize total earliness and tardiness

This paper considers the problem of scheduling a given number of jobs on a single machine to minimize total earliness and tardiness when family setup times exist. The paper proposes optimal branch-and-bound algorithms for both the group technology assumption and if the group technology assumption is removed. A heuristic algorithm is proposed to solve larger problems with the group technology assumption removed. The proposed algorithms were empirically evaluated on problems of various sizes and parameters. The paper also explores how the choice of procedure affects total earliness and tardiness if an implementation of lean production methods has resulted in a reduction in setup times. An important finding of these empirical investigations is that scheduling jobs by removing the group technology assumption can significantly reduce total earliness and tardiness.     

用GA算法解不同交货期窗口下的E/T调度问题

针对准时生产制下提前 /延迟 ( E/ T)费用的生产排序与调度问题 ,对不同交货期窗口下 E/ T指标的单机调度问题进行了分析 ,给出了在给定加工顺序条件下求解最优加工时间的动态规划算法。在此基础上 ,应用 GA( genetic al-gorithms)算法实现了求解。为提高算法优化性能 ,针对问题本身特性 ,分别从关键参数的选取 ;交叉操作的动态控制 ;变异操作的优化 3方面提出了相应改进策略。最后利用计算机仿真对算法性能进行研究 ,并得到一些经验性结论。仿真结果表明 ,该算法在优化性能和时间性能上均能满足工程上的要求。     

A branch-and-bound algorithm of the single machine schedule with sequence-dependent setup times for minimizing maximum tardiness

This paper addresses the NP-hard problem of scheduling N jobs on a single machine with due dates, sequence-dependent setup times and no preemption where the objective is to minimize the maximum tardiness. An algorithm based on branch-and-bound permutation schemes is developed including the implementation of lower and upper bounding procedures, and three dominance rules. Computational experiments demonstrate the effectiveness of the algorithm. In the experiments, the impacts of control parameters to generate test instances on algorithm performance (CPU times) are studied by statistics methods.     

Resource constraint scheduling with a fractional shared resource

We consider a scheduling problem motivated by mining in remote off-grid areas. In this model, mines have pre-assigned mineral processing jobs and their own machine for executing these jobs. Each job also needs a certain amount of electricity in order to get completed. The electricity, on the other hand, is of limited supply and must be shared between the mines. We present a mathematical formulation of the problem and a Lagrangian relaxation based heuristic. Computational results which compares our heuristic with genetic algorithm and simulated annealing are also presented.     

MDD函数在单机总误工排序问题中的作用

本文把工件的修正工期（MDD：Modified Due Date）看成工件关于时间的函数，通过研究该函数在一定区间的性质建立了一个具有全局意义的定理，利用这个定理可以方便地导出有关单机总误工排序问题的一些重要结论．这些工作既能够很好地解释常用的MI）D规则的有效性，同时也说明MDD函数可以成为解决单机总误工排序问题的基本工具．     

Scheduling two agents with controllable processing times

We consider several two-agent scheduling problems with controllable job processing times, where agents A and B have to share either a single machine or two identical machines in parallel while processing their jobs. The processing times of the jobs of agent A are compressible at additional cost. The objective function for agent B is always the same, namely a regular function _fmax$f_{\text{max}}$. Several different objective functions are considered for agent A, including the total completion time plus compression cost, the maximum tardiness plus compression cost, the maximum lateness plus compression cost and the total compression cost subject to deadline constraints (the imprecise computation model). All problems are to minimize the objective function of agent A subject to a given upper bound on the objective function of agent B. These problems have various applications in computer systems as well as in operations management. We provide NP-hardness proofs for the more general problems and polynomial-time algorithms for several special cases of the problems.