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.     

Single-machine scheduling to minimize earliness and number of tardy jobs

This paper considers the problem of assigning a common due-date to a set of simultaneously available jobs and sequencing them on a single machine. The objective is to determine the optimal combination of the common due-date and job sequence that minimizes a cost function based on the assigned due-date, job earliness values, and number of tardy jobs. It is shown that the optimal due-date coincides with one of the job completion times. Conditions are derived to determine the optimal number of nontardy jobs. It is also shown that the optimal job sequence is one in which the nontardy jobs are arranged in nonincreasing order of processing times. An efficient algorithm of O(n logn) time complexity to find the optimal solution is presented and an illustrative example is provided. Finally, several extensions of the model are discussed.This research was supported in part by the Natural Sciences and Engineering Research Council of Canada under Grant OPG0036424. The authors are thankful to two anonymous referees for their constructive comments.     

Single machine scheduling to minimize total weighted earliness subject to minimal number of tardy jobs

Motivated by just-in-time manufacturing, we consider a single machine scheduling problem with dual criteria, i.e., the minimization of the total weighted earliness subject to minimum number of tardy jobs. We discuss several dominance properties of optimal solutions. We then develop a heuristic algorithm with time complexity O(n³) and a branch and bound algorithm to solve the problem. The computational experiments show that the heuristic algorithm is effective in terms of solution quality in many instances while the branch and bound algorithm is efficient for medium-size problems.     

Single-machine scheduling with deteriorating jobs and learning effects to minimize the makespan

This paper studies the single-machine scheduling problem with deteriorating jobs and learning considerations. The objective is to minimize the makespan. We first show that the schedule produced by the largest growth rate rule is unbounded for our model, although it is an optimal solution for the scheduling problem with deteriorating jobs and no learning. We then consider three special cases of the problem, each corresponding to a specific practical scheduling scenario. Based on the derived optimal properties, we develop an optimal algorithm for each of these cases. Finally, we consider a relaxed model of the second special case, and present a heuristic and analyze its worst-case performance bound.     

工件可自由下线最小化总完工时间的平行分批排序问题

考虑工件可自由下线最小化总完工时间的有界平行分批排序问题. 在该问题中, 一台平行批机器可以同时处理 b 个工件作为一个平行批, 这里b 是批容量, 一个批的加工时间等于分配给这个批的工件的最大加工时间. 关于可自由下线工件, 每一个工件的完工时间等于包含这个工件的批的开工时间与工件的加工时间的和. 也就是, 如果一个批B 有一个开工时间S, 那么包含在批B 中的每一个工件J_j 的开工时间定义为S, 而它的完工时间定义为S+p_j, 这里p_j 是工件J_j 的加工时间. 对此问题, 首先研究最优排序的一些性质. 然后, 基于这些性质, 给出一个运行时间为O(n^{b (b-1)})的动态规划算法.     

Single-machine scheduling with deteriorating functions for job processing times

In many realistic scheduling settings a job processed later consumes more time than when it is processed earlier – this phenomenon is known as scheduling with deteriorating jobs. In the literature on deteriorating job scheduling problems, majority of the research assumed that the actual job processing time of a job is a function of its starting time. In this paper we consider a new deterioration model where the actual job processing time of a job is a function of the processing times of the jobs already processed. We show that the single-machine scheduling problems to minimize the makespan and total completion time remain polynomially solvable under the proposed model. In addition, we prove that the problems to minimize the total weighted completion time, maximum lateness, and maximum tardiness are polynomially solvable under certain agreeable conditions.     

Single-machine scheduling problems with an actual time-dependent deterioration

In this paper, we consider the single machine scheduling problems with an actual time-dependent deterioration effect. By the actual time-dependent deterioration effect, we mean that the processing time of a job is defined by increasing function of total actual processing time of jobs in front of it in the sequence. We show that even with the introduction of an actual time-dependent deterioration to job processing times, makespan minimization problem, total completion time minimization problem, the total lateness, and the sum of the quadratic job completion times minimization problem remain polynomially solvable, respectively. We also show that the total weighted completion time minimization problem, the discounted total weighted completion time minimization problem, the maximum lateness minimization problem, and the total tardiness minimization problem can be solved in polynomial time under certain conditions.     

Parallel-machine scheduling with simple linear deterioration to minimize total completion time

We consider the parallel-machine scheduling problem in which the processing time of a job is a simple linear increasing function of its starting time. The objective is to minimize the total completion time. We give a fully polynomial-time approximation scheme (FPTAS) for the case with m identical machines, where m is fixed. This study solves an open problem that has been posed in the literature for ten years.     

Single-machine scheduling with linear decreasing deterioration to minimize earliness penalties

We consider a single-machine scheduling problem with linear decreasing deterioration in which the due dates are determined by the equal slack (SLK) method. By the linear decreasing deterioration, we mean that the job’s processing time is a decreasing function of its starting time. The objective is to minimize the total weighted earliness penalty subject to no tardy jobs. We prove that two special cases of the problem remain polynomially solvable. The first case is the problem with equally weighted monotonous penalty objective function and the other case is the problem with weighted linear penalty objective function.     

Single-machine scheduling problems with both deteriorating jobs and learning effects

In this paper we consider the single-machine scheduling problems with job-position-based and sum-of-processing-times based processing times. The real processing time of a job is a function of its position and the total processing time of the jobs that are in front of it in the sequence. The objective is to minimize the makespan, and to minimize the mean finish time. We prove that some special cases are polynomially solvable under some restrictions of the parameters. In addition, for some another special cases of minimization of the mean finish time and the makespan, we show that an optimal schedule is V-shaped with respect to job normal processing times. Then, we propose a heuristic based on the V-shaped property, and show through a computational experiment that it performs efficiently.     

Learning effect and deteriorating jobs in the single machine scheduling problems

This paper studies the single machine scheduling problems with learning effect and deteriorating jobs simultaneously. In this model, the processing times of jobs are defined as functions of their starting times and positions in a sequence. It is shown that even with the introduction of learning effect and deteriorating jobs to job processing times, the makespan, the total completion time and the sum of the k$k$th power of completion times minimization problems remain polynomially solvable, respectively. But for the following objective functions: the total weighted completion time and the maximum lateness, this paper proves that the shortest weighted processing time first (WSPT) rule and the earliest due-date first (EDD) rule can construct the optimal sequence under some special cases, respectively.     

Two-parallel machines scheduling with rate-modifying activities to minimize total completion time

This paper considers the two-parallel machines scheduling problem with rate-modifying activities. In this model, each machine has a rate-modifying activity that can change the processing rate of machine under consideration. Hence the actual processing times of jobs vary depending on whether the job is scheduled before or after the rate-modifying activity. We need to make a decision on when to schedule the rate-modifying activities and the sequence of jobs to minimize some objective function. We provide polynomial and pseudo-polynomial time algorithms to solve the total completion time minimization problem and total weighted completion time minimization problem under agreeable ratio condition.     

Single-machine scheduling with convex resource dependent processing times and deteriorating jobs

In this study, we consider scheduling problems with convex resource dependent processing times and deteriorating jobs, in which the processing time of a job is a function of its starting time and its convex resource allocation. The objective is to find the optimal sequence of jobs and the optimal convex resource allocation separately. This paper focus on the single-machine problems with objectives of minimizing a cost function containing makespan, total completion time, total absolute differences in completion times and total resource cost, and a cost function containing makespan, total waiting time, total absolute differences in waiting times and total resource cost. It shows that the problems remain polynomially solvable under the proposed model.     

Single machine quadratic penalty function scheduling with deteriorating jobs and group technology

This paper considers single machine scheduling problems with group technology (GT) and deteriorating jobs. We consider the case of jobs whose processing times are a simple linear function of their starting time. The two objectives of scheduling problems are to minimize the weighted sum of squared completion times and the weighted sum of squared waiting times, respectively. We also provide polynomial time algorithms to solve these problems.     

NP-hardness of the single-variable-resource scheduling problem to minimize the total weighted completion time

Baker and Nuttle [K.R. Baker, H.L.W. Nuttle, Sequencing independent jobs with a single resource, Naval Research Logistics Quarterly 27 (1980) 499–510] studied the following single-variable-resource scheduling problem: sequencing n jobs for processing by a single resource to minimize a function of job completion times, when the availability of the resource varies over time. When the objective function to be minimized is the total weighted completion time, Baker and Nuttle conjectured that the problem is NP-hard. We show in this note that the conjecture is true.     

Minimizing the weighted number of early and tardy jobs in a stochastic single machine scheduling problem

We study a static stochastic single machine scheduling problem in which jobs have random processing times with arbitrary distributions, due dates are known with certainty, and fixed individual penalties (or weights) are imposed on both early and tardy jobs. The objective is to find an optimal sequence that minimizes the expected total weighted number of early and tardy jobs. The general problem is NP-hard to solve; however, in this paper, we develop certain conditions under which the problem is solvable exactly. An efficient heuristic is also introduced to find a candidate for the optimal sequence of the general problem. Our illustrative examples and computational results demonstrate that the heuristic performs well in identifying either optimal sequences or good candidates with low errors. Furthermore, we show that special cases of the problem studied here reduce to some classical stochastic single machine scheduling problems including the problem of minimizing the expected weighted number of early jobs and the problem of minimizing the expected weighted number of tardy jobs which are both solvable by the proposed exact or heuristic methods.     

On-line scheduling to minimize average completion time revisited

We consider the scheduling problem of minimizing the average-weighted completion time on identical parallel machines when jobs are arriving over time. For both the preemptive and the nonpreemptive setting, we show that straightforward extensions of Smith's ratio rule yield smaller competitive ratios than the previously best-known deterministic on-line algorithms.     

On-line scheduling of unit time jobs with rejection: minimizing the total completion time

We consider on-line scheduling of unit time jobs on a single machine with job-dependent penalties. The jobs arrive on-line (one by one) and can be either accepted and scheduled, or be rejected at the cost of a penalty. The objective is to minimize the total completion time of the accepted jobs plus the sum of the penalties of the rejected jobs.We give an on-line algorithm for this problem with competitive ratio . Moreover, we prove that there does not exist an on-line algorithm with competitive ratio better than 1.63784.     

Single-machine ready times scheduling with group technology and proportional linear deterioration

Scheduling research has increasingly taken the concept of deterioration into consideration. In this paper, we study a single machine group scheduling problem with deterioration effect, where the jobs are already put into groups, before any optimization. We assume that the actual processing times of jobs are increasing functions of their starting times, i.e., the job processing times are described by a function which is proportional to a linear function of time. The setup times of groups are assumed to be fixed and known. For some special cases of minimizing the makespan with ready times of the jobs, we show that the problem can be solved in polynomial time for the proposed model. For the general case, a heuristic algorithm is proposed, and the computational experiments show that the performance of the heuristic is fairly accurately in obtaining near-optimal solutions. The results imply that the average percentage error of the proposed heuristic algorithm from optimal solutions is less than 3%.