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In this paper, we address single-machine scheduling with sum of logarithm processing times-based learning effect. Under exponential past-sequence-dependent delivery times, we proved that the makespan and total completion time minimizations can be solved by the smallest processing time (SPT) first rule. Under the agreeable weight condition and agreeable due date condition, we show that the total weighted completion time minimization and maximum tardiness minimization can be solved in polynomial time, respectively. [ABSTRACT FROM AUTHOR]

This paper addresses the single-machine scheduling with general truncated learning effects (GTLE) and delivery times that are past sequence dependent (DT psd) . The objective is to determine an optimal job schedule such that makespan, sum of the β th power of job completion times, and total weighted completion time are minimized, where β > 0 is a given constant. We proved that the makespan, the sum of the β th power of job completion times, and a special case of the total weighted completion time can be solved in polynomial time. For the general case of the total weighted completion time, we propose the heuristic, simulated annealing and branch-and-bound algorithms. Extensive numerical experiments validate the efficiency of the proposed solution algorithms on a set of randomly generated instances. Furthermore, the computational experiment is also conducted to show that the simulated annealing performs effectively and efficiently. [ABSTRACT FROM AUTHOR]

This paper investigates single-machine scheduling with a deteriorating maintenance activity, where the processing time of a job depends on whether it is handled before or after the maintenance activity. Under common and slack due date assignments, the aim is to find the optimal job schedule, position of the maintenance activity, and optimal value of the common due date (flow-allowance) so that the linear weighted sum of earliness, tardiness and common due date (flow-allowance) value is minimized, where the weights are location-dependent (position-dependent) weights. Through a series of optimal properties, a polynomial time algorithm is proposed and it is then proven that the problem is polynomially solvable. [ABSTRACT FROM AUTHOR]

We study the problem of two-machine no-wait flowshop scheduling with learning effect and convex resource-dependent processing times. Under the condition of the due-date assignment with common flow allowance (i.e. slack (SLK) due-date assignment), we provide a bi-criteria analysis where the first criterion is to minimise the scheduling criteria (i.e. the weighted sum of earliness, tardiness and flow allowance costs), and the second criterion is to minimise the resource consumption cost (i.e. the weighted sum of resource consumption cost). The objective is to determine the optimal job sequence, resource allocations and common (flow allowance) slack time that minimise the three different versions of the two criteria. We prove that these problems can be solved in polynomial time. [ABSTRACT FROM AUTHOR]

This paper considers a group scheduling problem with shorten (i.e., a proportional linear shortening) job processing times and ready times on a single machine. If the jobs are in the same group, they have independent and constant ready times. The setup time of a group is independent constant setup time between each group. The goal is to determine the optimal group sequence and the job sequence within the groups such that the makespan (i.e., the maximum completion time) is minimized. For the general case of the problem, an initial heuristic algorithm (an upper bound) and some lower bounds are proposed, and then a branch-and-bound algorithm can be developed to solve the problem. [ABSTRACT FROM AUTHOR]

Scheduling problems with variable processing times and past-sequence-dependent delivery times are considered on a single-machine. The delivery times of jobs depend on their waiting times of processing. A job's actual processing time depends on its position in a sequence, its starting time and its allocation of non-renewable resources. Under the linear resource consumption function, the goal (version) is to determine the optimal sequence and optimal resource allocation such that the sum of scheduling cost and total resource consumption cost is minimized. Under the convex resource consumption function, three versions of the scheduling cost and total resource consumption cost are discussed. We prove that these four versions can be solved in polynomial time, respectively. Some applications are also given by using the scheduling cost, which involve the makespan, total completion time, total absolute differences in completion times (TADC), and total absolute differences in waiting times (TADW). [ABSTRACT FROM AUTHOR]

This article considers single-machine problems in which the actual processing time of a job is a function of its position in a sequence (i.e. position-dependent deterioration effects). In this model, a job is either accepted or rejected. If the job is accepted, it is processed on a single machine, but if the job is rejected, a penalty (cost) is imposed. The goal is to minimize the sum of the given scheduling objectives, including the makespan, the total completion time, the total absolute differences in completion times and the total absolute differences in waiting times of the accepted jobs and total rejection penalty of the rejected jobs. It is illustrated that these problems remain polynomially solvable under the proposed models. Finally, computational results demonstrate that the proposed algorithms can solve instances of various size problems in attractive times. An extension to the problems is offered by assuming time-dependent deterioration effects. [ABSTRACT FROM AUTHOR]

We study resource allocation scheduling with job-dependent learning effect on a single machine with or without due date assignment considerations. For a convex resource processing time function, we provide a polynomial time algorithm to find the optimal job sequence, and resource allocations that minimise the schedule criterion (the total compression cost) subject to the constraint that the total compression cost (the schedule criterion) is less than or equal to a fixed amount. [ABSTRACT FROM PUBLISHER]

This article deals with an integrated optimization problem of production scheduling and common due-window assignment on a single machine. The objective is to minimize the total cost, which is a weighted sum function of earliness and tardiness, due-window starting time, and due-window size, where the weights only depend on their position in a sequence (i.e. position-dependent weights). A polynomial time solution algorithm is provided for the corresponding problem. The problem can also be extended to slack due-windows assignment and general position-dependent processing times. It is proved that both these extensions remain polynomially solvable. [ABSTRACT FROM AUTHOR]

This article addresses permutation flowshop scheduling problems with simple linear deterioration. The objectives are to minimize logarithm of the makespan, total logarithm of the completion time, total weighted logarithm of the completion time, and the sum of the quadratic job logarithms of the completion times. Approximation algorithms and their worst-case bounds are presented and analysed. Branch-and-bound algorithms are also proposed to solve the problems optimally. Computational experiments are performed to illustrate the algorithms. [ABSTRACT FROM AUTHOR]

The permutation flow shop problems with truncated exponential sum of logarithm processing times based and position‐based learning effects are considered in this study. The objective is to minimize makespan and total weighted completion time, respectively. Several heuristics and a branch‐and‐bound algorithm are proposed in this paper. The tight worst‐case bounds of some simple heuristics are also given. Numerical experiments are tested to evaluate the performance of the heuristics and branch‐and‐bound algorithm. [ABSTRACT FROM AUTHOR]

This paper considers a single-machine scheduling problem with deteriorating jobs and convex resource allocation. We assume that the actual processing time of a job is a function of its convex resource allocation and its starting time. For the multi-objective single-machine scheduling problem, we show that the problem is polynomially solvable in O (n log n) time, where n is the total number of jobs. [ABSTRACT FROM AUTHOR]

We investigate a group scheduling problem with shortening job processing times on a single machine in which the shortening is proportional-linear shortening and the setup time of a group is fixed. For the maximum completion time (i.e. the makespan) minimization problem with ready times, we show that the general case of the problem can be solved in polynomial time if the number of groups is a given constant. We also prove that some special cases of the problem can be optimally solved by a lower order algorithm respectively. [ABSTRACT FROM AUTHOR]

This paper considers a scheduling problem with general job-dependent learning curves and controllable processing times on a single machine. The objective is to determine the optimal compressions of the processing times and the optimal sequence of jobs so as to minimize some total cost functions, which consist of regular and non-regular functions and the processing time compressions. It shows that the problem can be solved by an assignment problem and thus can be solved in polynomial time. Some extensions of the problem are also given. [ABSTRACT FROM AUTHOR]

In this article, single-machine group scheduling with learning effects and convex resource allocation is studied. The goal is to find the optimal job schedule, the optimal group schedule, and resource allocations of jobs and groups. For the problem of minimizing the makespan subject to limited resource availability, it is proved that the problem can be solved in polynomial time under the condition that the setup times of groups are independent. For the general setup times of groups, a heuristic algorithm and a branch-and-bound algorithm are proposed, respectively. Computational experiments show that the performance of the heuristic algorithm is fairly accurate in obtaining near-optimal solutions. [ABSTRACT FROM AUTHOR]

The focus of this paper is to analyze unrelated parallel-machine resource allocation scheduling problem with learning effect and deteriorating jobs. The goal is to find the optimal sequence of jobs and the optimal resource allocation separately for minimizing the cost function including the total load, the total completion time, the total absolute deviation of completion time and the total resource cost. We show that the problem is polynomial time solvable if the number of machines is a given constant. [ABSTRACT FROM AUTHOR]

The note deals with machine scheduling problems with a more general learning effect model, i.e., the actual job processing time is a function of the sum of the function of the processing times of the jobs already processed and job position. We show that some single machine scheduling problems are still polynomially solvable under the proposed model. We also show that some special cases of the flow shop scheduling problems can be solved in polynomial time. [ABSTRACT FROM AUTHOR]

We consider a single-machine common due-window assignment scheduling problem, in which the processing time of a job is a function of its position in a sequence and its resource allocation. The window location and size, along with the associated job schedule that minimizes a certain cost function, are to be determined. This function is made up of costs associated with the window location, window size, earliness, and tardiness. For two different processing time functions, we provide a polynomial time algorithm to find the optimal job sequence and resource allocation, respectively. [ABSTRACT FROM AUTHOR]

In this study, we consider a permutation flow shop scheduling problem on a three-machine with deteriorating jobs (a deteriorating job means that the job's processing time is an increasing function of its starting time) so as to minimize the makespan. We model job deterioration as a function that is proportional to a linear function of time. For some special cases, we prove that the problem can be solved in polynomial time. We develop branch-and-bound and heuristic procedures for the general case. Computational experiments for the branch-and-bound algorithm and heuristic algorithm are presented. [ABSTRACT FROM AUTHOR]

In this paper, we consider a two-machine flow shop scheduling problem with decreasing linear deterioration. By decreasing linear deterioration, we mean that the processing time is a decreasing function of its execution start time. The objective is to find a sequence that minimizes the total weighted completion time. Several dominance properties and some lower bounds are derived to speed up the elimination process of a branch-and-bound algorithm. Two heuristic algorithms are also proposed to overcome the inefficiency of the branch-and-bound algorithm. Computational results for randomly generated problem instances are presented. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we consider single-machine scheduling problems with position-dependent processing times, i.e., jobs whose processing times are an increasing or decreasing function of their positions in a processing sequence. In addition, the jobs are related by parallel chains and a series–parallel graph precedence constraints, respectively. It is shown that for the problems of minimization of the makespan polynomial algorithms exist. [Copyright &y& Elsevier]

The single-machine slack due date scheduling problem with deteriorating jobs is researched, where the deterioration effect means that the actual processing time of jobs is defined as increasing function of their starting time and the deteriorating rates of all jobs are identical, and due date of the job is equal to its actual processing time plus the common slack time. The objective is to determine the optimal scheduling and the common slack time simultaneously to minimize the sum of earliness, tardiness and common slack. time. It is proved that the problem can be transformed into the product of two vectors by the operations research method, thus can be solved in polynomial time, and the optimal algorithm to solve the problem is given. [ABSTRACT FROM AUTHOR]

We consider single-machine scheduling problem in which the processing time of a job is a function of its position in a sequence, its starting time, and its resource allocation. The objective is to find the optimal sequence of jobs and the optimal resource allocation separately. We concentrate on two goals separately, namely, minimizing a cost function containing makespan, total completion time, total absolute differences in completion times, and total resource cost; minimizing a cost function containing makespan, total waiting time, total absolute differences in waiting times, and total resource cost. The problem is modeled as an assignment problem, and thus can be solved in polynomial time. Some extensions of the problem are also shown. [ABSTRACT FROM AUTHOR]

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In this paper we investigate a single machine scheduling problem with deteriorating jobs and group technology assumption. By deteriorating jobs and group technology assumption, we mean that job processing times are simple linear functions of its starting times. The group setup times are assumed to be known and fixed. We attempt to minimize the makespan with ready times of the jobs. For a special case, we show that the problem can be solved in polynomial time when deterioration and group technology are considered simultaneously. [ABSTRACT FROM AUTHOR]

Abstract: We consider single-machine scheduling problems in which the processing time of a job is a function of its starting time and its resource allocation. The objective is to find the optimal sequence of jobs and the optimal resource allocation separately. We concentrate on two goals separately, namely, minimizing a cost function containing makespan, total completion time, total absolute differences in completion times and total resource cost; minimizing a cost function containing makespan, total waiting time, total absolute differences in waiting times and total resource cost. We show that the problems remain polynomially solvable under the proposed model. [Copyright &y& Elsevier]

A real industrial production phenomenon, referred to as learning effects, has drawn increasing attention. However, most research on this issue considers only single machine problems. Motivated by this limitation, this paper considers flow shop scheduling problems with a general position-dependent learning effects. By the general position-dependent learning effects, we mean that the actual processing time of a job is defined by a general non-increasing function of its scheduled position. The objective is to minimize one of the five regular performance criteria, namely, the total completion time, the makespan, the total weighted completion time, the total weighted discounted completion time, and the sum of the quadratic job completion times. We present heuristic algorithms by using the optimal permutations for the corresponding single machine scheduling problems. We also analyze the worst-case bound of our heuristic algorithms. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we consider a single-machine common due-window assignment scheduling problem with learning effect and deteriorating jobs. In this model, job processing times are defined by functions of their starting times and positions in the sequence. The window location and size, along with the associated job schedule that minimizes a certain cost function, are to be determined. This function is made up of costs associated with the window location, window size, earliness and tardiness. We show that the problem remains polynomially solvable under the proposed model. [Copyright &y& Elsevier]

Abstract: In this paper we consider the single machine past-sequence-dependent (p-s-d) setup times scheduling problems with general position-dependent and time-dependent learning effects. By the general position-dependent and time-dependent learning effects, we mean that the actual processing time of a job is not only a function of the total normal processing times of the jobs already processed, but also a function of the job’s scheduled position. The setup times are proportional to the length of the already processed jobs. We consider the following objective functions: the makespan, the total completion time, the sum of the θth (θ ⩾0) power of job completion times, the total lateness, the total weighted completion time, the maximum lateness, the maximum tardiness and the number of tardy jobs. We show that the problems of makespan, the total completion time, the sum of the θth (θ ⩾0) power of job completion times and the total lateness can be solved by the smallest (normal) processing time first (SPT) rule, respectively. We also show that the total weighted completion time minimization problem, the maximum lateness minimization problem, maximum tardiness minimization problem and the number of tardy jobs minimization problem can be solved in polynomial time under certain conditions. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we address a two-machine flow shop scheduling problem under simple linear deterioration. By a simple linear deterioration function, we mean that the processing time of a job is a simple linear function of its execution start time. The objective is to find a sequence that minimizes total weighted completion time. Optimal schedules are obtained for some special cases. For the general case, several dominance properties and two lower bounds are derived to speed up the elimination process of a branch-and-bound algorithm. A heuristic algorithm is also proposed to overcome the inefficiency of the branch-and-bound algorithm. Computational analysis on randomly generated problems is conducted to evaluate the branch-and-bound algorithm and heuristic algorithm. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we consider the problem of simultaneous determination of optimal due dates and optimal schedule for the single machine problem with multiple common due dates. The penalty for a job is assumed to be a linear function of the due date and the earliness/tardiness for the job. The objective function is to minimize the total penalty for all jobs. We show that with the introduction of learning to job processing times the problem remains polynomially solvable for a given number of multiple common due dates. [Copyright &y& Elsevier]

Abstract: In this paper we consider single-machine scheduling problems with an exponential sum-of-actual-processing-time-based learning effect. By the exponential sum-of-actual-processing-time-based learning effect, we mean that the processing time of a job is defined by an exponential function of the sum of the actual processing times of the already processed jobs. For the proposed learning model, we show that under certain conditions, the makespan minimization problem, the sum of the th () powers of completion times minimization problem, and some special cases of the total weighted completion time minimization problem and the maximum lateness minimization problem all remain polynomially solvable. [ABSTRACT FROM AUTHOR]

Abstract: 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. [Copyright &y& Elsevier]

Abstract: In this study we consider the single-machine scheduling problems with a sum of-processing-times-based learning effect. The sum of-processing-times-based learning effect of a job is assumed to be a function of the sum of the normal processing time of the already processed jobs. The objective is to minimize one of two regular objective functions, namely the weighted sum of completion times and the maximum lateness. We use the weighted shortest processing time (WSPT) rule and the earliest due date (EDD) rule as heuristics for the general cases and analyze their worst-case error bounds. We also provide computational results to evaluate the performance of the heuristics. [Copyright &y& Elsevier]

Abstract: In this paper we consider a single-machine scheduling problem with the effects of learning and deterioration. In this model, job processing times are defined by functions of their starting times and positions in the sequence. The problem is to determine an optimal combination of the due-date and schedule so as to minimize the sum of earliness, tardiness and due-date. We show that the problem remains polynomially solvable under the proposed model. [Copyright &y& Elsevier]

Abstract: 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. [Copyright &y& Elsevier]

Abstract: 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 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. [Copyright &y& Elsevier]

Abstract: This paper deals with single-machine scheduling problems with decreasing linear deterioration, i.e., jobs whose processing times are a decreasing function of their starting times. In addition, the jobs are related by parallel chains and a series–parallel graph precedence constraints, respectively. It is shown that for the problems of minimization of the makespan, polynomial algorithms exist. [Copyright &y& Elsevier]

Abstract: This paper deals with some special cases of general, no-wait and no-idle permutation flow shop scheduling problems, respectively. Special cases means that the machines form an increasing series of dominant machines, a decreasing series of dominant machines, an increasing–decreasing series of dominant machines and a decreasing–increasing series of dominant machines. Efficient polynomial time algorithms for finding the optimal schedules to minimize discounted total weighted completion time are developed. [Copyright &y& Elsevier]

Abstract: This paper considers a two-machine flow shop scheduling problem with deteriorating jobs. By a deteriorating job, we mean that the processing time of a job is an increasing function of its execution start time. A simple linear deterioration function is assumed. The objective is to find a sequence that minimizes total completion time. Optimal solutions are obtained for some special cases. For the general case, several dominance properties and two lower bounds are derived to speed up the elimination process of a branch-and-bound algorithm. A heuristic algorithm is also proposed to overcome the inefficiency of the branch-and-bound algorithm. Computational results show that the proposed heuristic algorithm performs effectively and efficiently. [Copyright &y& Elsevier]

Abstract: In this paper, we consider a single machine scheduling problem with a common due date. Job processing times are controllable to the extent that they can be reduced, up to a certain limit, at a cost proportional to the reduction. The common due date, along with the associated job schedule that minimizes a certain cost function, are to be determined. This function is made up of costs associated with the common due date, processing time reduction as well as job absolute value in lateness. We show that the problem can be formulated as an assignment problem and thus can be solved with well-known algorithms. For the case that where all the jobs have a common difference between normal and crash processing time and an equal unit compression penalty, we present an O(n log n) algorithm to obtain the optimal solution. [Copyright &y& Elsevier]

The purpose of this paper is to point out that the jobs in the scheduling problem considered in Yin et al. (Int J Adv Manuf Technol 46:707-714, ) may not be deteriorating jobs. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we investigate a single machine scheduling problem with decreasing time-dependent processing times and group technology assumption. By the decreasing time-dependent processing times and group technology assumption, we mean that the group setup times and job processing times are both decreasing linear functions of their starting times. We want to minimize the makespan subject to release dates. We show that the problem can be solved in polynomial time. [Copyright &y& Elsevier]

Abstract: In this paper we consider the scheduling problem with a general exponential learning effect and past-sequence-dependent (p-s-d) setup times. By the general exponential learning effect, we mean that the processing time of a job is defined by an exponent function of the total weighted normal processing time of the already processed jobs and its position in a sequence, where the weight is a position-dependent weight. The setup times are proportional to the length of the already processed jobs. We consider the following objective functions: the makespan, the total completion time, the sum of the δ ⩾0th power of completion times, the total weighted completion time and the maximum lateness. We show that the makespan minimization problem, the total completion time minimization problem and the sum of the quadratic job completion times minimization problem can be solved by the smallest (normal) processing time first (SPT) rule, respectively. We also show that the total weighted completion time minimization problem and the maximum lateness minimization problem can be solved in polynomial time under certain conditions. [Copyright &y& Elsevier]

Abstract: In this paper we consider the single-machine scheduling problems with both learning and deterioration effects. By the effects of learning and deterioration, we mean that job processing times are defined by functions of their starting times and positions in the sequence. It is shown that even with the introduction of learning effect and deteriorating jobs to job processing times, single-machine makespan minimization problem and the sum of the θth power of job completion times minimization problem remain polynomially solvable, respectively. But for the following objective functions: the weighted sum of completion times and the maximum lateness, this paper proves that the WSPT rule and the EDD rule can construct the optimal sequence under some special cases, respectively. [Copyright &y& Elsevier]