Due-date assignment and maintenance activity scheduling problem

In the scheduling problem addressed in this note we have to determine: (i) the job sequence, (ii) the (common) due-date, and (iii) the location of a rate modifying (maintenance) activity. Jobs scheduled before (after) the due-date are penalized according to their earliness (tardiness) value. The processing time of a job scheduled after the maintenance activity decreases by a job-dependent factor. The objective is minimum total earliness, tardiness and due-date cost. We introduce a polynomial (O(n⁴)) solution for the problem.     

A note on optimal assignment of slack due-dates in single-machine scheduling

This paper extends T.C.E. Cheng's approach for optimal assignment of slack due-dates and sequencing in the single-machine shop to the case when preemption is allowed and there are precedence constraints and ready times of jobs. It is shown that under special conditions the presented algorithm may be used when preemption is not allowed.     

Batch scheduling and common due-date assignment on a single machine

We consider the problem of scheduling n groups of jobs on a single machine where three types of decisions are combined: scheduling, batching and due-date assignment. Each group includes identical jobs and may be split into batches; jobs within each batch are processed jointly. A sequence independent machine set-up time is needed between each two consecutively scheduled batches of different groups. A due-date common to all jobs has to be assigned. A schedule specifies the size of each batch, i.e. the number of jobs it contains, and a processing order for the batches. The objective is to determine a value for the common due-date and a schedule so as to minimize the sum of the due date assignment penalty and the weighted number of tardy jobs. Several special cases of this problem are shown to be ordinary NP-hard. Some cases are solved in O(n log n) time. Two pseudopolynomial dynamic programming algorithms are presented for the general problem, as well as a fully polynomial approximation scheme.     

Due-window assignment with identical jobs on parallel uniform machines

A scheduling problem with a common due-window, earliness and tardiness costs, and identical processing time jobs is studied. We focus on the setting of both (i) job-dependent earliness/tardiness job weights and (ii) parallel uniform machines. The objective is to find the job allocation to the machines and the job schedule, such that the total weighted earliness and tardiness cost is minimized. We study both cases of a non-restrictive (i.e. sufficiently late), and a restrictive due-window. For a given number of machines, the solutions of the problems studied here are obtained in polynomial time in the number of jobs.     

A due-date assignment problem with learning effect and deteriorating jobs

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.     

Scheduling identical jobs and due-window on uniform machines

We extend a classical common due-window assignment problem to a setting of parallel uniform machines. Jobs are assumed to have identical processing times. The objective is minimum earliness, tardiness, due-window starting time, and due-window size. We focus on the case of two machines. Despite the many (12) candidate schedules for optimality, an efficient constant time solution is introduced.     

Optimal preemptive scheduling on uniform machines with discounted flowtime objectives

We consider the problem of scheduling n jobs on m parallel machines. Each job has a deterministic processing time and a weight associated with it. For uniform machines we show that discounted flowtime is minimized by serving jobs preemptively in increasing order of their remaining processing times, assigning the job with the shortest remaining processing time to the fastest available machine.     

Parallel machine scheduling with nested job assignment restrictions

We derive a polynomial time approximation scheme for a special case of makespan minimization on unrelated machines.     

Fast LP models and algorithms for identical jobs on uniform parallel machines

Scheduling n identical jobs on m uniform parallel machines to minimize scheduling work is very common in practice. The case of identical jobs is common in manufacturing systems, in which many products have identical designs or processing times on the same machine. Factories often buy new equipment but retain their slower, older equipment; this results in machines having different processing speeds.     

Preemptive scheduling of two uniform parallel machines to minimize total tardiness

We consider the problem of preemptive scheduling n jobs on two uniform parallel machines. All jobs have equal processing requirements. For each job we are given its due date. The objective is to find a schedule minimizing total tardiness ∑T_i. We suggest an O(n log n) algorithm to solve this problem.     

Batch scheduling and common due date assignment problem: An NP-hard case

An important special case of the problem studied in Cheng and Kovalyov (1996) arises when there are equal set-up times and equal job processing times. Computational complexity of this case was indicated to be open, however. I prove its NP-hardness.     

Preemptive scheduling of equal length jobs with release dates on two uniform parallel machines

We consider a problem of scheduling n jobs on two uniform parallel machines. For each job we are given its release date when the job becomes available for processing. All jobs have equal processing requirements. Preemptions are allowed. The objective is to find a schedule minimizing total completion time. We suggest an O(n³) algorithm to solve this problem.     

Due-date assignment and parallel-machine scheduling with deteriorating jobs

In this paper we study the problem of scheduling n deteriorating jobs on m identical parallel machines. Each job's processing time is a nondecreasing function of its start time. The problem is to determine an optimal combination of the due-date and schedule so as to minimize the sum of the due-date, earliness and tardiness penalties. We show that this problem is NP-hard, and we present a heuristic algorithm to find near-optimal solutions for the problem. When the due-date penalty is 0, we present a polynomial time algorithm to solve it.     

A note on the two-stage assembly flow shop scheduling problem with uniform parallel machines

We study the problem of minimizing the makespan in a two-stage assembly flow shop scheduling problem with uniform parallel machines. This problem is a generalization of the assembly flow shop problem with concurrent operations in the first stage and a single assembly operation in the second stage. We propose a heuristic with an absolute performance bound which becomes asymptotically optimal as the number of jobs becomes very large. We show that our results slightly improve earlier results for the simpler assembly flow shop problem (without uniform machines) and for the two-stage hybrid flow shop problem with uniform machines.     

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

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

Safe scheduling: Setting due dates in single-machine problems

We consider single-machine stochastic scheduling models with due dates as decisions. In addition to showing how to satisfy given service-level requirements, we examine variations of a model in which the tightness of due-dates conflicts with the desire to minimize tardiness. We show that a general form of the trade-off includes the stochastic E/T model and gives rise to a challenging scheduling problem. We present heuristic solution methods based on static and dynamic sorting procedures. Our computational evidence identifies a static heuristic that routinely produces good solutions and a dynamic rule that is nearly always optimal. The dynamic sorting procedure is also asymptotically optimal, meaning that it can be recommended for problems of any size.     

Optimal workforce assignment to operations of a paced assembly line

We study a paced assembly line intended for manufacturing different products. Workers with identical skills perform non-preemptable operations whose assignment to stations is known. Operations assigned to the same station are executed sequentially, and they should follow the given precedence relations. Operations assigned to different stations can be performed in parallel. The operation’s processing time depends on the number of workers performing this operation. The problem consists in assigning workers to operations such that the maximal number of workers employed simultaneously in the assembly line is minimized, the line cycle time is not exceeded and the box constraints specifying the possible number of workers for each operation are not violated. We show that the general problem is NP-hard in the strong sense, develop conventional and randomized heuristics, propose a reduction to a series of feasibility problems, present a MILP model for the feasibility problem, show relation of the feasibility problem to multi-mode project scheduling and multiprocessor scheduling, establish computational complexity of several special cases based on this relation and provide computer experiments with real and simulated data.     

Due-date assignment and single machine scheduling with deteriorating jobs

We study a scheduling problem with deteriorating jobs, that is, jobs whose processing times are an increasing function of their start times. We consider the case of a single machine and linear job-independent deterioration. The problem is to determine an optimal combination of the due-date and schedule so as to minimize the sum of due-date, earliness and tardiness penalties. We give an O(n log n) time algorithm to solve this problem.     

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

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