Search

This paper studies the single-machine scheduling problem with truncated learning effect, time-dependent processing time, and past-sequence-dependent delivery time. The delivery time is the time that the job is delivered to the customer after processing is complete. The goal is to determine an optimal job schedule to minimize the total weighted completion time and maximum tardiness. In order to solve the general situation of the problem, we propose a branch-and-bound algorithm and other heuristic algorithms. Computational experiments also prove the effectiveness of the given algorithms. [ABSTRACT FROM AUTHOR]

In classical schedule problems, the actual processing time of a job is a fixed constant, but in the actual production process, the processing time of a job is affected by a variety of factors, two of which are the learning effect and resource allocation. In this paper, single-machine scheduling problems with resource allocation and a time-dependent learning effect are investigated. The actual processing time of a job depends on the sum of normal processing times of previous jobs and the allocation of non-renewable resources. With the convex resource consumption function, the goal is to determine the optimal schedule and optimal resource allocation. Three problems arising from two criteria (i.e., the total resource consumption cost and the scheduling cost) are studied. For some special cases of the problems, we prove that they can be solved in polynomial time. More generally, we propose some accurate and intelligent algorithms to solve these problems. [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]

This article investigates the single-machine common due-window assignment problem with generalized earliness/tardiness penalties and a rate-modifying activity. Job processing times include two cases: one with constant values and another with time-dependent processing times (deterioration effect). Considering the maintenance activity, the maintenance time is a fixed constant. The goal is to determine the position of the common due window and the optimal sequence such that the following objective function is minimized: the weighted penalties for the sum of earliness and tardiness, the weighted number of early and delayed, and the weighted due-window starting time and size. It is proved that the problem can be solved in O (n 6) time, where n is the number of jobs. [ABSTRACT FROM AUTHOR]

This article addresses how to minimize total completion time on a single machine with a position-weighted learning effect. Under non-zero job release dates, a lower bound on the objective function, a number of dominance properties, and an initial solution (i.e. an NEH-based heuristic) are derived, which are used to expedite the elimination process of a branch-and-bound solution procedure. The performance of the branch-and-bound algorithm and the heuristic algorithm are evaluated on a set of randomly generated problem instances. [ABSTRACT FROM AUTHOR]

In this article, the two-machine no-wait permutation flowshop scheduling problem with common due window assignment, learning effect and resource allocation is considered, wherein learning effect and resource allocation mean that the processing time of a job is a function of its position in a sequence and its amount of resource allocation. According to the common due window assignment method, each job is associated with a common due window, which is a decision variable. The goal is to determine the sequence of jobs, common due window starting time, due window size and resource allocation such that the linear weighted sum of job earliness, tardiness, due window size and resource cost is minimized. This article shows that the scheduling problem can be solved in polynomial time. [ABSTRACT FROM AUTHOR]

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 the no-wait flowshop scheduling problem with simultaneous consideration of common due date assignment, convex resource allocation and learning effect in a two machine setting. The processing time of each job can be controlled by its position in a sequence and also by allocating extra resource, which is a convex function of the amount of a common continuously divisible resource allocated to the job. The objective is to determine the optimal common due date, the resource allocation and the schedule of jobs such that the total earliness, tardiness and common due date cost (the total resource consumption cost) are minimized under the constraint condition that the total resource consumption cost (the total earliness, tardiness and common due date cost) is limited. Polynomial time algorithms are developed for two versions of the problem. [ABSTRACT FROM AUTHOR]

This study considers a single machine group scheduling problem with deteriorating jobs and resource allocation (controllable processing times). The objective is to have the resource availability limited within a given range, and to minimize the maximum completion time (i.e. the makespan). For two special cases, it is proved that the problem can be solved in polynomial time. For the general case, an heuristic algorithm and a branch-and-bound algorithm are proposed. Computational results show that the proposed heuristic algorithm is generally effective. [ABSTRACT FROM AUTHOR]

This paper addresses resource allocation scheduling problems with CON/SLK due date assignment and job-dependent learning effects on a single machine. Two different resource consumption functions under common (denoted by CON) and slack (denoted by SLK) due date assignment are considered. The objective is to determine the optimal due dates of jobs, a sequence for jobs and resource allocation of jobs to minimize a total cost function. The optimality properties for all problems and polynomial time algorithms are proposed to solve these problems. [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]

In this study we consider the problem of scheduling n jobs on m unrelated parallel processors with deterioration effect. We allow an option for performing a modifying (i.e. deteriorating) maintenance activity on each machine, i.e. the job normal processing times will be changed following this modifying maintenance activity. We need to make a decision on when to schedule the modifying maintenance activities and the sequence of jobs so as to minimize a cost function containing total completion (waiting) time, total absolute differences in completion (waiting) times, and total machine load. We show that the problem remains polynomially solvable under the proposed model. [ABSTRACT FROM AUTHOR]

A facile silver-catalyzed decarboxylative radical addition/cyclization reaction of α,α-difluoroarylacetic acids and acrylamides has been disclosed. The method provides a highly attractive approach to synthesize a series of difluorinated oxindoles that contain various functional groups in moderate to good yields under mild conditions. Moreover, experimental studies reveal that the CF2 group of the α,α-difluoroarylacetic acids plays a vital role in the transformation. [ABSTRACT FROM AUTHOR]

A cascade C−N, C−C and C−O multiple-bond-formation reaction to synthesize 3-acylindoles from 2-alkenylanilines with DMF ( N,N-dimethylformamide) as a one-carbon synthon is described. This approach employed dioxygen as a terminal oxidant and oxygen donor, generally provided the 3-acylindoles in moderate to good yields. Moreover, the mechanistic investigation unambiguously revealed that the 2-carbon of 3-acylindole was derived from the N-methyl group of DMF. [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]

In enterprise management, there are often multiple agents competing for the same products to reduce production cost. On this basis, this paper investigates a two-agent slack due-date single-machine scheduling problem with deteriorating jobs, where the processing time of a job is extended as a function of position-dependent workload, resource allocation and a common deterioration rate. The goal is to find the optimal sequence and resource allocation that minimizes the maximal value of earliness, tardiness, and decision variables of one agent subject to an upper bound on cost value of the second agent. Through theoretical analysis, a polynomial time algorithm with O (N 3) time is proposed for the problem, where N is the maximum number of jobs between the two agents. [ABSTRACT FROM AUTHOR]

This paper deals with single machine scheduling problems with simple linear deterioration in which the processing time of a job is a simple linear function of its execution starting time. The objective is to determine the optimal schedule to minimize the weighted sum of the θ th ( θ is a positive integer number) power of waiting times. It is proved that the general problem can be solved in polynomial time. In addition, for the jobs with weak (strong) parallel chains and a series–parallel digraph precedence constraints, it is also proved that these problems can be solved in polynomial time, respectively. [ABSTRACT FROM AUTHOR]

Single-machine due-window assignment scheduling with delivery times and variable processing times is investigated, where the variable processing time of a job means that the processing time is a function of its position in a sequence and its resource allocation. Currently, there are multiple optimization objectives for the due-window assignment problem, and there is a small amount of research on optimization problems where the window starting time, the rejected cost and the optimal scheduling are jointly required. The goal of this paper is to minimize the weighed sum of scheduling cost, resource consumption cost and outsourcing measure under the optional job outsourcing (rejection). Under two resource allocation models (i.e., linear and convex resource allocation models), the scheduling cost is the weighted sum of the number of early–tardy jobs, earliness–tardiness penalties and due-window starting time and size, where the weights are positional-dependent. The main contributions of this paper include the study and data simulation of single-machine scheduling with learning effects, delivery times and outsourcing cost. For the weighed sum of scheduling cost, resource consumption cost and outsourcing measure, we prove the polynomial solvability of the problem. Under the common and slack due-window assignments, through the theoretical analysis of the optimal solution, we reveal that four problems can be solved in O (n 6) time, where n is the number of jobs. [ABSTRACT FROM AUTHOR]

Abstract: 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). [Copyright &y& Elsevier]

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: The single-machine scheduling problems with position and sum-of-processing-time based processing times are considered. The actual processing time of a job is defined by function of its scheduled position and total normal processing time of jobs in front of it in the sequence. We provide optimal solutions in polynomial time for some special cases of the makespan minimization and the total completion time minimization. We also show that an optimal schedule to be a V-shaped schedule in terms of the normal processing times of jobs for the total completion time minimization problem and the makespan minimization problem. [Copyright &y& Elsevier]

Abstract: The paper deals with machine scheduling problems with a general learning effect. By the general learning effect, we mean that the actual processing time of a job is not only a non-increasing function of the total weighted normal processing times of the jobs already processed, but also a non-increasing function of the job’s position in the sequence, where the weight is a position-dependent weight. We show that even with the introduction of a general learning effect to job processing times, 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. [Copyright &y& Elsevier]

Abstract: The purpose of this study is to explore the single-machine scheduling with the effects of exponential learning and general deterioration. By the effects of exponential learning and general deterioration, we meant that job processing time is decided by the functions of their starting time and positions in the sequence. Results showed that with the introduction of learning effect and deteriorating jobs to job processing time, single-machine makespan, and sum of completion time (square) minimization problems remained polynomially solvable, respectively. But for the following objective functions: the weighted sum of completion time and the maximum lateness, this paper proved that the weighted smallest basic processing time first (WSPT) rule and the earliest due date first (EDD) rule constructed the optimal sequence under some special cases, respectively. [Copyright &y& Elsevier]

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]

Under just-in-time production, this paper studies a single machine common due-window (denoted by CONW) assignment scheduling problem with position-dependent weights and resource allocations. A job's actual processing time can be determined by the resource assigned to the job. A resource allocation model is divided into linear and convex resource allocations. Under the linear and convex resource allocation models, our goal is to find an optimal due-window location, job sequence and resource allocation. We prove that the weighted sum of scheduling cost (including general earliness–tardiness penalties with positional-dependent weights) and resource consumption cost minimization is polynomially solvable. In addition, under the convex resource allocation, we show that scheduling (resp. resource consumption) cost minimization is solvable in polynomial time subject to the resource consumption (resp. scheduling) cost being bounded. [ABSTRACT FROM AUTHOR]

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]

In this article, we consider a single machine scheduling problem with a time-dependent learning effect and deteriorating jobs. By the effects of time-dependent learning and deterioration, we mean that the job processing time is defined by a function of its starting time and total normal processing time of jobs in front of it in the sequence. The objective is to determine an optimal schedule so as to minimize the total completion time. This problem remains open for the case of −1 < a < 0, where a denotes the learning index; we show that an optimal schedule of the problem is V-shaped with respect to job normal processing times. Three heuristic algorithms utilising the V-shaped property are proposed, and computational experiments show that the last heuristic algorithm performs effectively and efficiently in obtaining near-optimal solutions. [ABSTRACT FROM PUBLISHER]

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 identical parallel machines scheduling problems with a deteriorating maintenance activity. In this model, each machine has a deteriorating maintenance activity, that is, delaying the maintenance increases the time required to perform it. 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 concentrate on two goals separately, namely, minimizing the total absolute differences in completion times (TADC) and the total absolute differences in waiting times (TADW). We show that the problems remain polynomially solvable under the proposed model. [Copyright &y& Elsevier]

Abstract: In this paper, we consider the single-machine scheduling problems with a time-dependent deterioration. By the time-dependent deterioration, we mean that the processing time of a job is defined by an increasing function of total normal processing time of jobs in front of it in the sequence. The objective is to minimize the total completion time. We develop a mixed integer programming formulation for the problem. The complexity status of this problem remains open. Hence, we use the smallest normal processing time (SPT) first rule as a heuristic algorithm for the general cases and analyze its worst-case error bound. Two heuristic algorithms utilize the V-shaped property are also proposed to solve the problem. Computational results are presented to evaluate the performance of the proposed algorithms. [ABSTRACT FROM AUTHOR]

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 show that the main results in a recent paper by Zhang and Yan [X. Zhang and G. Yan, Machine scheduling problems with a general learning effect, Mathematical and Computer Modelling 51 (2010) 84–90] are incorrect as an important reason is missing, that is, the processing time of a job is variable according to a general learning effect. Here we point out these wrong results by a counter-example. In addition, we give a revised model with a general learning effect. We show that some single machine scheduling problems are still polynomially solvable under the revised model. We also show that some special cases of the flowshop scheduling problems can be solved in polynomial time under the revised model. [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 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. [Copyright &y& Elsevier]

Abstract: In this paper we consider the single machine scheduling problems with exponential sum-of-logarithm-processing-times based learning effect. By the exponential sum-of-logarithm-processing-times based learning effect, we mean that the processing time of a job is defined by an exponent function of the sum of the logarithm of the processing times of the jobs already processed. We consider the following objective functions: the makespan, the total completion time, the sum of the quadratic job 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 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: In this paper we consider the single machine scheduling problem with exponential time-dependent learning effect and past-sequence-dependent (p-s-d) setup times. By the exponential time-dependent learning effect, we mean that the processing time of a job is defined by an exponent function of the total normal processing time of the already processed jobs. 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 quadratic job 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 study we consider the single-machine scheduling problem 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 times of the already processed jobs. We prove that the shortest processing time (SPT) rule is optimal for the sum of completion times square minimization problem. We also show by examples that the optimal schedule for the classical version of the problem is not optimal in the presence of a sum-of-processing-times-based learning effect for the following three objective functions: the weighted sum of completion times, the maximum lateness and the number of tardy jobs. But for some special cases, we prove that the weighted shortest processing time (WSPT) rule, the earliest due date (EDD) rule and Moore’s algorithm can construct an optimal schedule for the problem to minimize these objective functions, respectively. [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]