Optimal due-date assignment problem with learning effect and resource-dependent processing times

In this paper, we consider a single-machine earliness-tardiness scheduling problem with due-date assignment, in which the processing time of a job is a function of its position in a sequence and its resource allocation. The due date assignment methods studied include the common due date, and the slack due date, which reflects equal waiting time allowance for the jobs. For each combination of due date assignment method and processing time function, we provide a polynomial-time algorithm to find the optimal job sequence, due date values, and resource allocations that minimize an integrated objective function, which includes earliness, tardiness, due date assignment, and total resource consumption costs.     

带学习效应和资源依赖的单机排序模型

在工业生产中,随着员工操作技能的熟练程度的增加,对于相同的任务越往后加工,所花的时间将会减少。 同时,为了尽早完工,管理者也会考虑给加工工件分配一定量的额外资源来缩短工件加工时间。 本文基于以上实例,讨论了工件的实际加工时间既具有学习效应又依赖所分配资源的单机排序问题。 在问题中,假设工件的学习效应是之前已加工工件正常加工时间和的指数函数。 同时随着分配给工件资源量的增加,工件的实际加工时间呈线性减少,所需费用呈线性增加。对这一排序模型,主要探讨以下五个目标函数:最小化最大完工时间与资源消耗量总费用的和;最小化总完工时间与资源消耗量总费用的和;最小化加权总完工时间与资源消耗量总费用的和;最小化总提前、总延误、总共同交货期与资源消耗量总费用的和以及最小化总提前、总延误、总松弛交货期与资源消耗量总费用的和。 本文对前三个目标函数相应的排序问题给出了多项式时间可求解的算法。 对后两个目标函数所涉及的排序问题借助于指派问题分别给出了时间复杂性为O(n³)的算法。     

具有CON/SLK交货期指派的一类单机排序问题

研究工件的实际加工时间既具有指数学习效应,又依赖所消耗资源的准时制排序问题.在模型中,探讨了共同交货期(CON)和松弛交货期(SLK)两种情形.管理者的目标是确定最优序、最优资源分配方案和最佳工期(共同交货期或松弛交货期)以便极小化工件的总延误、总提前、总工期和资源消耗费用的总和.对于工件的实际加工时间是资源消耗量的线性函数的排序问题,通过将其转化为指派模型,给出了时间复杂性为O(n~3)的算法,从而证明该类排序问题是多项式时间可求解的.针对工件的实际加工时间是资源消耗量的凸函数的排序问题,也给出了多项式算法.     

具有老化效应的单机共同工期安排和工件可拒绝排序问题

研究共同工期安排和具有老化效应的单机排序问题。在整个加工过程中,工件的实际加工时间是与其所在位置和工件本身老化率相关的函数,生产商可以通过支付一定的处罚费用而拒绝加工某些工件。鉴于生产过程中出现老化效应,通过采取维修活动来提高生产率。目标是划分接受工件集和拒绝工件集,确定接受工件集中工件的加工次序和维修活动安排的位置,以极小化接受工件的提前、延误、工期与拒绝工件的总处罚费用的加权和。对这一问题,首先将其转化为指派问题并构造了最优多项式时间算法;其次,证明了目标函数满足一定条件下的问题的更一般形式能够在多项式时间内得到最优解;最后,对本文问题的一个特殊情况,设计了具有更低时间复杂度的多项式动态规划算法。     

Single machine SLK/DIF due window assignment problem with learning effect and deteriorating jobs

We study a single-machine scheduling and due window assignment problem, in which job processing times are defined by functions of their starting times (deteriorating effect) and positions in the sequence (learning effect). The problem is to determine the optimal due windows and the processing sequence simultaneously to minimize costs for earliness, tardiness, the window location, window size and makespan. We show that the problem remains polynomially solvable under the proposed model for two popular due window assignment methods: The slack due date assignment method (usually referred to as SLK) and the unrestricted due date assignment method (usually referred to as DIF).     

A unified approach for scheduling with convex resource consumption functions using positional penalties

We provide a unified model for solving single machine scheduling problems with controllable processing times in polynomial time using positional penalties. We show how this unified model can be useful in solving three different groups of scheduling problems. The first group includes four different due date assignment problems to minimize an objective function which includes costs for earliness, tardiness, due date assignment, makespan and total resource consumption. The second group includes three different due date assignment problems to minimize an objective function which includes the weighted number of tardy jobs, due date assignment costs, makespan and total resource consumption costs. The third group includes various scheduling problems which do not involve due date assignment decisions. We show that each of the problems from the first and the third groups can be reduced to a special case of our unified model and thus can be solved in O(n³)$O(n^3)$ time. Furthermore, we show how the unified model can be used repeatedly as a subroutine to solve all problems from the second group in O(n⁴)$O(n^4)$ time. In addition, we also show that faster algorithms exist for several special cases.     

Minimizing the weighted number of tardy jobs with due date assignment and capacity-constrained deliveries for multiple customers in supply chains

In this paper, an integrated due date assignment and production and batch delivery scheduling problem for make-to-order production system and multiple customers is addressed. Consider a supply chain scheduling problem in which n orders (jobs) have to be scheduled on a single machine and delivered to K customers or to other machines for further processing in batches. A common due date is assigned to all the jobs of each customer and the number of jobs in delivery batches is constrained by the batch size. The objective is to minimize the sum of the total weighted number of tardy jobs, the total due date assignment costs and the total batch delivery costs. The problem is NP-hard. We formulate the problem as an Integer Programming (IP) model. Also, in this paper, a Heuristic Algorithm (HA) and a Branch and Bound (B&B) method for solving this problem are presented. Computational tests are used to demonstrate the efficiency of the developed methods.     

带凸资源和恶化效应的单机松弛窗口排序

研究带凸资源和恶化效应的单机窗口指派排序问题,其中窗口指的是松弛窗口,凸资源和恶化效应指的是工件的实际加工时间是其开始加工时间的线性函数,是其资源消耗量的凸函数。目标是确定工件的加工顺序,资源分配量以及窗口的开始加工时间和长度使其在总资源消耗费用(与窗口有关的排序费用)有上界限制的条件下,极小化与窗口有关的排序费用(总资源消耗费用)。获得了求解上述问题的最优算法,证明了该问题是多项式时间可解的。     

Single machine scheduling and due date assignment with positionally dependent processing times

We consider single machine scheduling and due date assignment problems in which the processing time of a job depends on its position in a processing sequence. The objective functions include the cost of changing the due dates, the total cost of discarded jobs that cannot be completed by their due dates and, possibly, the total earliness of the scheduled jobs. We present polynomial-time dynamic programming algorithms in the case of two popular due date assignment methods: CON and SLK. The considered problems are related to mathematical models of cooperation between the manufacturer and the customer in supply chain scheduling.     

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.     

A faster algorithm for a due date assignment problem with tardy jobs

The single-machine due date assignment problem with the weighted number of tardy jobs objective, (the TWNTD problem), and its generalization with resource allocation decisions and controllable job processing times have been solved in O(n⁴) time by formulating and solving a series of assignment problems. In this note, a faster O(n²) dynamic programming algorithm is proposed for the TWNTD problem and for its controllable processing times generalization in the case of a convex resource consumption function.     

Two due date assignment problems in scheduling a single machine

We study two single-machine scheduling problems: minimizing the sum of weighted earliness, tardiness and due date assignment penalties and minimizing the weighted number of tardy jobs and due date assignment costs. We prove that both problems are strongly NP-hard and give polynomial solutions for some important special cases.     

Single machine scheduling problems with general position-dependent processing times and past-sequence-dependent delivery times

This paper considers single machine scheduling with past-sequence-dependent (psd) delivery times, in which the processing time of a job depends on its position in a sequence. We provide a unified model for solving single machine scheduling problems with psd delivery times. We first show how this unified model can be useful in solving scheduling problems with due date assignment considerations. We analyze the problem with four different due date assignment methods, the objective function includes costs for earliness, tardiness and due date assignment. We then consider scheduling problems which do not involve due date assignment decisions. The objective function is to minimize makespan, total completion time and total absolute variation in completion times. We show that each of the problems can be reduced to a special case of our unified model and solved in O(n ³) time. In addition, we also show that each of the problems can be solved in O(nlogn) time for the spacial case with job-independent positional function.     

Fast algorithms for scheduling with learning effects and time-dependent processing times on a single machine

We consider scheduling problems with learning/deterioration effects and time-dependent processing times on a single machine, with or without due date assignment considerations. By reducing them to a special assignment problem on product matrices, we solve all these problems in near-linear time. This improves the time complexity of previous algorithms for some scheduling problems and establishes the fast polynomial solvability for several other problems.     

Single machine common flow allowance scheduling with controllable processing times

In this paper, we consider single machine SLK due date assignment scheduling problem in which job processing times are controllable variables with linear costs. The objective is to determine the optimal sequence, the optimal common flow allowance and the optimal processing time compressions to minimize a total penalty function based on earliness, tardiness, common flow allowance and compressions. We solve the problem by formulating it as an assignment problem which is polynomially solvable. For some special cases, we present an O(n logn) algorithm to obtain the optimal solution respectively.     

Single machine scheduling problem with multiple due windows assignment in a group technology

We consider group scheduling problem on a single machine with multiple due windows assignment. Jobs are divided into groups in advance according to their processing similarities, and all jobs of the same group are required to be processed contiguously on the machine in order to achieve production efficiency and save time/money resource. A sequence-independent setup time precedes the processing of each group. The goal is to determine the optimal sequence for both groups and jobs, together with an optimal combination of the due windows assignment strategy so as to minimize the total of earliness, tardiness and due windows related costs. We give an \(O(n\log n)\) time algorithm for the problem.     

Minimizing the weighted number of tardy jobs and maximum tardiness in relocation problem with due date constraints

The relocation problem addressed in this paper is to determine a reconstruction sequence for a set of old buildings, under a limited budget, such that there is adequate temporary space to house the residents decanted during rehabilitation. It can be regarded as a resource-constrained scheduling problem where there is a set of jobs to be processed on a single machine. Each job demands a number of resources for processing and returns probably a different number of resources on its completion. Given a number of initial resources, the problem seeks to determine if there is a feasible sequence for the successful processing of all the jobs. Two generalizations of the relocation problem in the context of single machine scheduling with due date constraints are studied in this paper. The first problem is to minimize the weighted number of tardy jobs under a common due date. We show that it is NP-hard even when all the jobs have the same tardy weight and the same resource requirement. A dynamic programming algorithm with pseudo-polynomial computational time is proposed for the general case. In the second problem, the objective is to minimize the maximum tardiness when each job is associated with an individual due date. We prove that it is strongly NP-hard. We also propose a pseudo-polynomial time dynamic programming algorithm for the case where the number of possible due dates is predetermined.     

Single-machine due window assignment and scheduling with a common flow allowance and controllable job processing time

In this paper, we consider single-machine due window assignment and scheduling with a common flow allowance and controllable job processing times, subject to unlimited or limited resource availability. Due window assignment with a common flow allowance means that each job has a job-dependent due window, the starting time and completion time of which are equal to its actual processing time plus the job-independent parameters q₁ and q₂, respectively, which are common to all the jobs. The processing time of each job is either a linear or a convex function of the amount of a common continuously divisible resource allocated to the job. We study five versions of the problem that differ in terms of the objective function and processing time function being used. We provide structural properties of the optimal schedules and polynomial-time solution algorithms for the considered problems.     

Job sequencing and due date assignment in a single machine shop with uncertain processing times

This paper considers due date assignment and sequencing for multiple jobs in a single machine shop. The processing time of each job is assumed to be uncertain and is characterized by a mean and a variance with no knowledge of the entire distribution. A heuristic procedure is developed to find job sequence and due date assignment to minimize a linear combination of three penalties: penalty on job earliness, penalty on job tardiness, and penalty associated with long due date assignment. Numerical experiments indicate that the performance of the procedure is stable and robust to job processing time distributions. In addition, the performance improves when the means and variances of job processing times are uncorrelated or negatively correlated or when the penalty of a long due date assignment is significant.     

极大化提前完工总量平行机排序问题的LPT算法

研究带有共同交货期的三台平行机排序问题。工件在加工过程中不允许中断, 目标是极大化所有工件的提前完工量, 即在交货期前所加工工件(或部分) 的总加工时长。由于该问题是NP-难问题, 本文应用经典LPT算法来解决该问题。我们证明了LPT算法求解该问题的最坏情况界至多为$\frac{15}{13}$, 并给出实例说明最坏情况界的下界为$\frac{27}{25}$。