Scheduling controllable processing time jobs in a deteriorating environment

In many real-life applications, job processing times are a function of the waiting time prior to their execution. In the most general setting, each job comprises of a basic processing time, which is independent of its start time, and a start time-dependent deterioration function. Some common examples of deteriorating systems include fire fighting, pollution containment, and medical treatments. To date, research has focused on scheduling models where the basic processing time of jobs is constant. However, job processing times are often controllable through the allocation of a limited non-renewable resource. We study a single-machine setting that combines these two models under the assumptions of general linear deterioration and convex resource functions. We develop a polynomial time solution for minimizing the makespan. For the total flowtime criterion, we compute the optimal resource allocation policy for a given job instance and show that the sequencing problem is at least as hard as the case with non-controllable jobs. We follow by discussing the properties of several special cases.     

Batch scheduling with controllable setup and processing times to minimize total completion time

We study a problem of scheduling n jobs on a single machine in batches. A batch is a set of jobs processed contiguously and completed together when the processing of all jobs in the batch is finished. Processing of a batch requires a machine setup time dependent on the position of this batch in the batch sequence. Setup times and job processing times are continuously controllable, that is, they are real-valued variables within their lower and upper bounds. A deviation of a setup time or job processing time from its upper bound is called a compression. The problem is to find a job sequence, its partition into batches, and the values for setup times and job processing times such that (a) total job completion time is minimized, subject to an upper bound on total weighted setup time and job processing time compression, or (b) a linear combination of total job completion time, total setup time compression, and total job processing time compression is minimized. Properties of optimal solutions are established. If the lower and upper bounds on job processing times can be similarly ordered or the job sequence is fixed, then O(n³ log n) and O(n⁵) time algorithms are developed to solve cases (a) and (b), respectively. If all job processing times are fixed or all setup times are fixed, then more efficient algorithms can be devised to solve the problems.     

A note on single-machine scheduling with decreasing time-dependent job processing times

In this note we consider some single-machine scheduling problems with decreasing time-dependent job processing times. Decreasing time-dependent job processing times means that its processing time is a non-increasing function of its execution start time. We present polynomial solutions for the sum of squared completion times minimization problem, and the sum of earliness penalties minimization problem subject to no tardy jobs, respectively. We also study two resource constrained scheduling problems under the same decreasing time-dependent job processing times model and present algorithms to find their optimal solutions.     

Single machine group scheduling with time and position dependent processing times

In the paper two resource constrained single-machine group scheduling problems with time and position dependent processing times are considered. By time and position dependent processing times and group technology assumption, we mean that the processing time of a job is defined by the function of its starting time and position in the group, and the group setup times of a group is a positive strictly decreasing continuous function of the amount of consumed resource. We present polynomial solutions for the makespan minimization problem under the constraint that the total resource consumption does not exceed a given limit, and the total resource consumption minimization problem under the constraint that the makespan does not exceed a given limit, respectively.     

Scheduling with time dependent processing times: Review and extensions

In classical scheduling theory job processing times are constant. However, there are many situations where processing time of a job depends on the starting time of the job in the queue. This paper reviews the rapidly growing literature on single machine scheduling models with time dependent processing times. Attention is focused on linear, piecewise linear and non-linear processing time functions for jobs. We survey known results and introduce new solvable cases. Finally, we identify the areas and give directions where further research is needed.     

Minimizing total completion time on a single machine with step improving jobs

Production systems often experience a shock or a technological change, resulting in performance improvement. In such settings, job processing times become shorter if jobs start processing at, or after, a common critical date. This paper considers a single machine scheduling problem with step-improving processing times, where the effects are job-dependent. The objective is to minimize the total completion time. We show that the problem is NP-hard in general and discuss several special cases which can be solved in polynomial time. We formulate a Mixed Integer Programming model and develop an LP-based heuristic for the general problem. Finally, computational experiments show that the proposed heuristic yields very effective and efficient solutions.     

Scheduling in a contaminated area: A model and polynomial algorithms

There are n jobs to be scheduled in a contaminated area. The jobs can be rescue, de-activation or cleaning works to be executed by a single worker in an area contaminated with radio-active or chemical materials. Precedence relations can be given on the set of jobs. An execution of each job can be preempted. However, the length of the minimal uninterrupted work period is given and it is the same for all jobs. Each work period for a job should be accompanied by a rest period whose length depends on the start time of the work period and its length. We focus on a short term planning problem. We show that this problem can be modelled by a scheduling problem with start time dependent job processing times. The dependency functions are exponentially decreasing ones. We also construct two polynomial time algorithms for the both cases—with and without precedence constraints.     

Scheduling jobs with position-dependent processing times

The paper is devoted to some single machine scheduling problems, where job processing times are defined by functions dependent on their positions in the sequence. It is assumed that each job is available for processing at its ready time. We prove some properties of the special cases of the problems for the following optimization criteria: makespan, total completion time and total weighted completion time. We prove strong NP-hardness of the makespan minimization problem for two different models of job processing time. The reductions are done from the well-known 3-Partition Problem. In order to solve the makespan minimization problems, we suggest the Earliest Ready Date algorithms, for which the worst-case ratios are calculated. We also prove that the makespan minimization problem with job ready times is equivalent to the maximum lateness minimization problem.     

A note on proving the strong NP-hardness of some scheduling problems with start time dependent job processing times

In this paper, we show that the strong NP-hardness proofs of some scheduling problems with start time dependent job processing times presented in Gawiejnowicz (Eur J Oper Res 180:472–478, 2007) and Zhao and Tang (Optim Lett 5:183–190, 2011) are incorrect. Namely, the applied transformations from 4-Product problem to the considered scheduling problems are polynomial not pseudopolynomial. Thus, the related problems are NP-hard, but their complete computational status is still an open issue: ordinary or strongly NP-hard?     

工件加工时间是开工时间线性函数的单机排序问题

研究了具有线性恶化工件的单机排序问题,其中线性恶化工件指的是工件的加工时间是开工时间的线性增长函数.在一般情况下,对目标函数为极小化完工时间平方和与极小化总误工数问题分别给出了最优算法.此外,在分段情况下,对目标函数为极小化最大完工时间问题也给出了最优算法.     

Single-machine scheduling with time window-dependent processing times

In the one-machine scheduling problems analysed in this paper, the processing time of a job depends on the time at which the job is started. More precisely, the horizon is divided into time windows and with each one a coefficient is associated that is used to determine the actual processing time of a job starting in it. Two models are introduced, and one of them has direct connections with models considered in previous papers on scheduling problems with time-dependent processing times. Various computational complexity results are presented for the makespan criterion, which show that the problem is NP-hard, even with two time windows. Solving procedures are also proposed for some special cases.     

Single machine scheduling problem with controllable processing times and resource dependent release times

We consider two single machine scheduling problems with resource dependent release times and processing times, in which the release times and processing times are linearly decreasing functions of the amount of resources consumed. The objective is to minimize the total cost of makespan and resource consumption function that is composed of release time reduction and processing time reduction. In the first problem, the cost of reducing a unit release time for each job is common. We show that the problem can be solved in polynomial time. The second problem assumes different reduction costs of job release times. We show that the problem can be reduced polynomially from the partition problem and thus, is NP-complete.     

A priority rule for minimizing weighted flow time in a class of parallel machine scheduling problems

The problem of scheduling n jobs with known process times on m identical parallel machines with an objective of minimizing weighted flow time is NP-hard. However, when job weights are identical, it is well known that the problem is easily solved using the shortest processing time rule. In this paper, we show that a generalization of the shortest processing time rule minimizes weighted flow time in a class of problems where job weights are not identical.     

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

This paper considers single-machine scheduling problems with job delivery times where the actual job processing time of a job is defined by a function dependent on its position in a schedule. We assume that the job delivery time is proportional to the job waiting time. We investigate the minimization problems of the sum of earliness, tardiness, and due-window-related cost, the total absolute differences in completion times, and the total absolute differences in waiting times on a single-machine setting. The polynomial time algorithms are proposed to optimally solve the above objective functions. We also investigate some special cases of the problem under study and show that they can be optimally solved by lower order algorithms.     

Single-machine scheduling problems with time and position dependent processing times

We consider single-machine scheduling problems with time and position dependent job processing times. In many industrial settings, the processing time of a job changes due to either job deterioration over time or machine/worker’s learning through experiences. In the models we study, each job has its normal processing time. However, a job’s actual processing time depends on when its processing starts and how many jobs have completed before its start. We prove that the classical SPT (Shortest Processing Time) rule remains optimal when we minimize the makespan or the total completion time. For problems of minimizing the total weighted completion time, the maximum lateness, and the discounted total weighted completion time, we present heuristic sequencing rules and analyze the worst-case bounds for performance ratios. We also show that these heuristic rules can be optimal under some agreeable conditions between the normal processing times and job due dates or weights.     

Some single-machine scheduling problems with actual time and position dependent learning effects

In this paper we study some single-machine scheduling problems with learning effects where the actual processing time of a job serves as a function of the total actual processing times of the jobs already processed and of its scheduled position. We show by examples that the optimal schedules for the classical version of problems are not optimal under this actual time and position dependent learning effect model for the following objectives: makespan, sum of kth power of the completion times, total weighted completion times, maximum lateness and number of tardy jobs. But under certain conditions, we show that the shortest processing time (SPT) rule, the weighted shortest processing time (WSPT) rule, the earliest due date (EDD) rule and the modified Moore’s Algorithm can also construct an optimal schedule for the problem of minimizing these objective functions, respectively.     

The strong NP-hardness of the maximum lateness minimization scheduling problem with the processing-time based aging effect

In this paper, we analyse the single machine maximum lateness minimization scheduling problem with the processing time based aging effect, where the processing time of each job is described by a non-decreasing function dependent on the sum of the normal processing times of preceded jobs. The computational complexity of this problem was not determined. However, we show it is strongly NP-hard by proving the strong NP-hardness of the single machine maximum completion time minimization problem with this aging model and job deadlines. Furthermore, we determine the boundary between polynomially solvable and NP-hard cases.     

Scheduling with controllable release dates and processing times: Total completion time minimization

The single machine scheduling problem with two types of controllable parameters, job processing times and release dates, is studied. It is assumed that the cost of compressing processing times and release dates from their initial values is a linear function of the compression amounts. The objective is to minimize the sum of the total completion time of the jobs and the total compression cost. For the problem with equal release date compression costs we construct a reduction to the assignment problem. We demonstrate that if in addition the jobs have equal processing time compression costs, then it can be solved in O(n²) time. The solution algorithm can be considered as a generalization of the algorithm that minimizes the makespan and total compression cost. The generalized version of the algorithm is also applicable to the problem with parallel machines and to a range of due-date scheduling problems with controllable processing times.     

Single-machine scheduling of multi-operation jobs without missing operations to minimize the total completion time

We consider the problem of scheduling multi-operation jobs on a singe machine to minimize the total completion time. Each job consists of several operations that belong to different families. In a schedule each family of job operations may be processed as batches with each batch incurring a set-up time. A job is completed when all of its operations have been processed. We first show that the problem is strongly NP-hard even when the set-up times are common and each operation is not missing. When the operations have identical processing times and either the maximum set-up time is sufficiently small or the minimum set-up time is sufficiently large, the problem can be solved in polynomial time. We then consider the problem under the job-batch restriction in which the operations of each batch is partitioned into operation batches according to a partition of the jobs. We show that this case of the problem can be solved in polynomial time under a certain condition.     

A polynomial time heuristic for the two-machine flowshop scheduling problem with setup times and random processing times

The two-machine flowshop scheduling problem to minimize makespan is addressed. Jobs have random processing times which are bounded within certain intervals. The distributions of job processing times are not known. This problem has been addressed in the literature with the assumption that setup times are included in processing times or are zero. In this paper, we relax this assumption and treat setup times as separate from processing times. We propose a polynomial time heuristic algorithm. Both Johnson algorithm and Yoshida and Hitomi algorithm, both of which developed for the deterministic problem, are special cases of the proposed algorithm. The heuristic algorithm uses a weighted average of lower and upper bounds for processing times. For different weights, the results of the proposed algorithm are compared based on randomly generated data. The computational analysis has shown that the proposed algorithm, with equal weights given to the lower and upper bounds, performs considerably well with an overall average error of 0.36%. The analysis has also shown that the proposed algorithm can safely be used regardless of processing time distributions and the range between lower and upper bounds.