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.     

Algorithms for two-machine flow-shop sequencing with precedence constraints

This paper considers the problem of minimizing the maximum completion time in a two-machine flow-shop for which precedence constraints on the jobs are specified. If one job has precedence over another, then the second of these jobs cannot be processed on a machine until the first of them is completed on that machine. A powerful new lower bounding rule which uses Lagrangean relaxation is developed. Then several dominance theorems are presented which are used to eliminate some jobs from the problem. The lower bound is used in three branch and bound algorithms, two of which employ well-known branching rules while the third uses a new branching rule. The algorithms are compared and tested on problems with up to 80 jobs.     

优先序约束的排序问题：基于最大匹配的近似算法

本文研究具有加工次序约束的单位工件开放作业和流水作业排序问题,目标函数为极小化工件最大完工时间。工件之间的加工次序约束关系可以用一个被称为优先图的有向无圈图来刻画。当机器数作为输入时,两类问题在一般优先图上都是强NP-困难的,而在入树的优先图上都是可解的。我们利用工件之间的许可对数获得了问题的新下界,并基于许可工件之间的最大匹配设计近似算法,其中匹配的许可工件对均能同时在不同机器上加工。对于一般优先图的开放作业问题和脊柱型优先图的流水作业问题,我们在理论上证明了算法的近似比为$2-\frac 2m$,其中$m$是机器数目。     

优先序约束的排序问题：基于最大匹配的近似算法

本文研究具有加工次序约束的单位工件开放作业和流水作业排序问题，目标函数为极小化工件最大完工时间。工件之间的加工次序约束关系可以用一个被称为优先图的有向无圈图来刻画。当机器数作为输入时，两类问题在一般优先图上都是强NP-困难的，而在入树的优先图上都是可解的。我们利用工件之间的许可对数获得了问题的新下界，并基于许可工件之间的最大匹配设计近似算法，其中匹配的许可工件对均能同时在不同机器上加工。对于一般优先图的开放作业问题和脊柱型优先图的流水作业问题，我们在理论上证明了算法的近似比为$2-\frac 2m$，其中$m$是机器数目。     

Maximization Problems in Single Machine Scheduling

Problems of scheduling n jobs on a single machine to maximize regular objective functions are studied. Precedence constraints may be given on the set of jobs and the jobs may have different release times. Schedules of interest are only those for which the jobs cannot be shifted to start earlier without changing job sequence or violating release times or precedence constraints. Solutions to the maximization problems provide an information about how poorly such schedules can perform. The most general problem of maximizing maximum cost is shown to be reducible to n similar problems of scheduling n?1 jobs available at the same time. It is solved in O(mn+n ²) time, where m is the number of arcs in the precedence graph. When all release times are equal to zero, the problem of maximizing the total weighted completion time or the weighted number of late jobs is equivalent to its minimization counterpart with precedence constraints reversed with respect to the original ones. If there are no precedence constraints, the problem of maximizing arbitrary regular function reduces to n similar problems of scheduling n?1 jobs available at the same time.     

Two machine preemptive scheduling problem with release dates,equal processing times and precedence constraints

We consider a scheduling problem with two identical parallel machines and n jobs. For each job we are given its release date when job becomes available for processing. All jobs have equal processing times. Preemptions are allowed. There are precedence constraints between jobs which are given by a (di)graph consisting of a set of outtrees and a number of isolated vertices. The objective is to find a schedule minimizing mean flow time. We suggest an O(n²) algorithm to solve this problem.The suggested algorithm also can be used to solve the related two-machine open shop problem with integer release dates, unit processing times and analogous precedence constraints.     

具有优先约束的单机随机排序问题

讨论工件的加工时间为常数,机器发生随机故障的单机随机排序问题,目标函数极小化工件的加权完工时间和的数学期望最小.考虑两类优先约束模型.在第一类模型中,设工件间的约束为串并有向图.证明了模块M的ρ因子最大初始集合I中的工件优先于模块中的其它工件加工,并且被连续加工所得的排序为最优排序,从而将Lawler用来求解约束为串并有向图的单机加权总完工时间问题的方法推广到机器发生随机故障的情况.在第二类模型中,设工件间的约束为出树优先约束.证明了最大家庭树中的工件优先于家庭树中其它的工件加工,并且其工件连续加工所得到的排序为最优排序并给出了最优算法.     

极小化最大提前完工费用的可中断排序问题

讨论了带截止期限的$n$个工件在单机上加工,工件间存在优先约束,在允许机器空闲的条件下,确定一个工件的可中断排序,极小化最大提前完工费用.首先考虑两种特殊情形:(1)截止期限相同,存在优先约束;(2)截止期限任意,不存在优先约束.针对两种情形分别给出了时间复杂度为$O(n^2)$的算法.在此基础上,考虑普遍情形,即截止期限任意,存在优先约束,也给出了一个时间复杂度为$O(n^2)$的算法.由于工件不允许延迟,问题可能会无可行排序,需先对问题的可行性进行讨论.     

航空器供油问题中完全逆序类中的多项式时间可解类

航空器供油问题是一类非线性组合优化问题,其目标函数为分式形式,该问题目前不存在多项式时间算法,也未被证明是NP完全问题。一般可以用置换来刻画n架飞机的一个供油顺序。该问题中有一类实例被称为“完全逆序类”,“完全逆序类”用动态规划算法求解计算时间为O(n2ⁿ),具有指数时间复杂度。本文通过对该“完全逆序类”问题做进一步分析,发现在“完全逆序类”中也存在着多项式时间可解的情况。定理1研究一类一次可解的情况,若问题满足定理1的条件,则求解一次即可找到其最优解;定理2研究一类多项式时间可解的情况,当问题满足定理2的条件时,其最优解可在多项式时间内获得。     

Approximability of single machine scheduling with fixed jobs to minimize total completion time

We consider the single machine scheduling problem to minimize total completion time with fixed jobs, precedence constraints and release dates. There are some jobs that are already fixed in the schedule. The remaining jobs are free to be assigned to any free-time intervals on the machine in such a way that they do not overlap with the fixed jobs. Each free job has a release date, and the order of processing the free jobs is restricted by the given precedence constraints. The objective is to minimize the total completion time. This problem is strongly NP-hard. Approximability of this problem is studied in this paper. When the jobs are processed without preemption, we show that the problem has a linear-time n-approximation algorithm, but no pseudopolynomial-time (1 − δ)n-approximation algorithm exists even if all the release dates are zero, for any constant δ > 0, if P ≠ NP, where n is the number of jobs; for the case that the jobs have no precedence constraints and no release dates, we show that the problem has no pseudopolynomial-time (2 − δ)-approximation algorithm, for any constant δ > 0, if P ≠ NP, and for the weighted version, we show that the problem has no polynomial-time 2^q(n)-approximation algorithm and no pseudopolynomial-time q(n)-approximation algorithm, where q(n) is any given polynomial of n. When preemption is allowed, we show that the problem with independent jobs can be solved in O(n log n) time with distinct release dates, but the weighted version is strongly NP-hard even with no release dates; the problems with weighted independent jobs or with jobs under precedence constraints are shown having polynomial-time n-approximation algorithms. We also establish the relationship of the approximability between the fixed job scheduling problem and the bin-packing problem.     

A Lagrangian relax-and-cut approach for the sequential ordering problem with precedence relationships

The sequential ordering problem with precedence relationships was introduced in Escudero [7]. It has a broad range of applications, mainly in production planning for manufacturing systems. The problem consists of finding a minimum weight Hamiltonian path on a directed graph with weights on the arcs, subject to precedence relationships among nodes. Nodes represent jobs (to be processed on a single machine), arcs represent sequencing of the jobs, and the weights are sums of processing and setup times. We introduce a formulation for the constrained minimum weight Hamiltonian path problem. We also define Lagrangian relaxation for obtaining strong lower bounds on the makespan, and valid cuts for further tightening of the lower bounds. Computational experience is given for real-life cases already reported in the literature.     

Lower Bounds for Scheduling a Single Robot in a Job-Shop Environment

We consider a single-machine scheduling problem which arises as a subproblem in a job-shop environment where the jobs have to be transported between the machines by a single transport robot. The robot scheduling problem may be regarded as a generalization of the traveling salesman problem with time windows, where additionally generalized precedence constraints (minimal time-lags) have to be respected. The objective is to determine a sequence of all nodes and corresponding starting times in the given time windows in such a way that all generalized precedence relations are respected and the sum of all traveling and waiting times is minimized.We calculate lower bounds for this problem using constraint propagation techniques and a linear programming formulation which is solved by a column generation procedure. Computational results are presented for test data arising from job-shop instances with a single transport robot and some modified traveling salesman instances.     

Scheduling jobs with chain precedence constraints and deteriorating jobs

In this paper we consider a single machine scheduling problem with deteriorating jobs. By deteriorating jobs, we mean that the processing time of a job is a simple linear function of its execution starting time. For the jobs with chain precedence constraints, we prove that the weighted sum of squared completion times minimization problem with strong chains and weak chains can be solved in polynomial time, respectively.     

Optimal stochastic single-machine-tardiness scheduling by stochastic branch-and-bound

A stochastic branch-and-bound technique for the solution of stochastic single-machine-tardiness problems with job weights is presented. The technique relies on partitioning the solution space and estimating lower and upper bounds by sampling. For the lower bound estimation, two different types of sampling (“within” and “without” the minimization) are combined. Convergence to the optimal solution (with probability one) can be demonstrated. The approach is generalizable to other discrete stochastic optimization problems. In computational experiments with the single-machine-tardiness problem, the technique worked well for problem instances with a relatively small number of jobs; due to the enormous complexity of the problem, only approximate solutions can be expected for a larger number of jobs. Furthermore, a general precedence rule for the single-machine scheduling of jobs with uncertain processing times has been derived, essentially saying that “safe” jobs are to be scheduled before “unsafe” jobs.     

带有链优先序的分批排序问题

本文首次就带有优先序的分批排序问题进行了讨论，目标函数为最大完工时间．当优先序为链，一条链上的工件个数为饨，而其它链的工件个数为常数，分批的容量B大于等于链的条数，在这种情况下，问题为多项式可解的．文中并讨论了几种特殊情况的多项式算法．     

Precedence constrained parallel-machine scheduling of position-dependent jobs

We consider parallel-machine job scheduling problems with precedence constraints. Job processing times are variable and depend on positions of jobs in a schedule. The objective is to minimize the maximum completion time or the total weighted completion time. We specify certain conditions under which the problem can be solved by scheduling algorithms applied earlier for fixed job processing times.     

Two-dedicated-machine scheduling problem with precedence relations to minimize makespan

Two-dedicated-parallel-machine scheduling problem with precedence constraints to minimize makespan is considered. This problem originally appeared as a sub-problem in assembly line balancing but it has also its own applications. Complexity and approximation results for this scheduling problem and its special cases with chains of jobs or equal-processing-times are presented.     

Reduction of job-shop problems to flow-shop problems with precedence constraints

We study the problem of scheduling N independent jobs in a job-shop environment. Each job must be processed on M machines according to individual routes. The objective is to minimize the maximum completion time of the jobs. First, the job-shop problem is reduced to a flow-shop problem with job precedence constraints. Then, a set of flow-shop algorithms are modified to solve it. To evaluate the quality of these heuristics, several lower bounds on the optimal solution have been computed and compared with the heuristic solutions for 3040 problems. The heuristics appear especially promising for job-shop problems with ‘flow-like’ properties.     

Parallel machine scheduling with a convex resource consumption function

We consider some problems of scheduling jobs on identical parallel machines where job-processing times are controllable through the allocation of a nonrenewable common limited resource. The objective is to assign the jobs to the machines, to sequence the jobs on each machine and to allocate the resource so that the makespan or the sum of completion times is minimized. The optimization is done for both preemptive and nonpreemptive jobs. For the makespan problem with nonpreemptive jobs we apply the equivalent load method in order to allocate the resources, and thereby reduce the problem to a combinatorial one. The reduced problem is shown to be NP-hard. If preemptive jobs are allowed, the makespan problem is shown to be solvable in O(n²) time. Some special cases of this problem with precedence constraints are presented and the problem of minimizing the sum of completion times is shown to be solvable in O(n log n) time.     

Preemptive Hybrid Flowshop Scheduling problem of interval orders

The Preemptive Hybrid (multi-processor) Flowshop Scheduling (PHFS) problem consists in preemptively scheduling n jobs in a flowshop subject to precedence constraints with the objective of minimizing the makespan. A special case of the general precedence constraints problems is NP-hard in the strong sense, Hoogeveen et al. [J.A. Hoogeveen, J.K. Lenstra, B. Veltman, European Journal of Operational Research 89 (1996) 172]. In this paper a class of precedence constraints is proposed for which the problem is polynomially solvable. The reported results demonstrate the feasibility and reliability of the proposed approach. This should open future prospects for developing approximation algorithms for any class of precedence constraints.