Scheduling jobs on parallel machines with sequence-dependent setup times

Consider a number of jobs to be processed on a number of identical machines in parallel. A job has a processing time, a weight and a due date. If a job is followed by another job, a setup time independent of the machine is incurred. A three phase heuristic is presented for minimizing the sum of the weighted tardinesses. In the first phase, as a pre-processing procedure, factors or statistics which characterize an instance are computed. The second phase consists of constructing a sequence by a dispatching rule which is controlled through parameters determined by the factors. In the third phase, as a post-processing procedure, a simulated annealing method is applied starting from a seed solution which is the result of the second phase. In the dispatching rule of the second phase there are two parameters of which the values are dependent on the particular problem instance at hand. Through extensive experiments rules are developed for determining the values of the two parameters which make the priority rule work effectively. The performance of the simulated annealing procedure in the third phase is evaluated for various values of the factors.     

Scheduling jobs with release dates on parallel batch processing machines

In this paper we consider the problem of scheduling jobs with release dates on parallel unbounded batch processing machines to minimize the maximum lateness. We show that the case where the jobs have deadlines is strongly NP-hard. We develop a polynomial-time approximation scheme for the problem to minimize the maximum delivery completion time, which is equivalent to minimizing the maximum lateness from the optimization viewpoint.     

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.     

A new dynamic programming formulation for scheduling independent tasks with common due date on parallel machines

This paper deals with a scheduling problem of independent tasks with common due date where the objective is to minimize the total weighted tardiness. The problem is known to be ordinary NP-hard in the case of a single machine and a dynamic programming algorithm was presented in the seminal work of Lawler and Moore [E.L. Lawler, J.M. Moore, A functional equation and its application to resource allocation and sequencing problems, Management Science 16 (1969) 77–84]. In this paper, this algorithm is described and discussed. Then, a new dynamic programming algorithm is proposed for solving the single machine case. These methods are extended for solving the identical and uniform parallel-machine scheduling problems.     

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.     

Unrelated parallel machines scheduling with deteriorating jobs and resource dependent processing times

We consider unrelated parallel machines scheduling problems involving resource dependent (controllable) processing times and deteriorating jobs simultaneously, i.e., the actual processing time of a job is a function of its starting time and its resource allocation. Two generally resource consumption functions, the linear and convex resource, were investigated. The objective is to find the optimal sequence of jobs and the optimal resource allocation separately. This paper focus on the objectives of minimizing a cost function containing makespan, total completion time, total absolute differences in completion times and total resource cost, and a cost function containing makespan, total waiting time, total absolute differences in waiting times and total resource cost. If the number of unrelated parallel machines is a given constant, we show that the problems remain polynomially solvable under the proposed model.     

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.     

Scheduling deteriorating jobs with a learning effect on unrelated parallel machines

In this study we consider unrelated parallel machines scheduling problems with learning effect and deteriorating jobs, in which the actual processing time of a job is a function of joint time-dependent deterioration and position-dependent learning. The objective is to determine the jobs assigned to corresponding each machine and the corresponding optimal schedule to minimize a cost function containing total completion (waiting) time, total absolute differences in completion (waiting) times and total machine load. If the number of machines is a given constant, we show that the problems can be solved in polynomial time under the time-dependent deterioration and position-dependent learning model.     

Scheduling parallel machines with inclusive processing set restrictions and job release times

We consider the problem of scheduling a set of jobs with different release times on parallel machines so as to minimize the makespan of the schedule. The machines have the same processing speed, but each job is compatible with only a subset of those machines. The machines can be linearly ordered such that a higher-indexed machine can process all those jobs that a lower-indexed machine can process. We present an efficient algorithm for this problem with a worst-case performance ratio of 2. We also develop a polynomial time approximation scheme (PTAS) for the problem, as well as a fully polynomial time approximation scheme (FPTAS) for the case in which the number of machines is fixed.     

Scheduling jobs with release dates on parallel batch processing machines to minimize the makespan

Batch processing happens in many different industries, in which a number of jobs are processed simultaneously as a batch. In this paper we develop two heuristics for the problem of scheduling jobs with release dates on parallel batch processing machines to minimize the makespan and analyze their worst-case performance ratios. We also present a polynomial-time optimal algorithm for a special case of the problem where the jobs have equal processing times.     

Homogeneously non-idling schedules of unit-time jobs on identical parallel machines

In this paper, we study the basic homogeneous $m$-machine scheduling problem where weakly dependent unit-time jobs have to be scheduled within the time windows between their release dates and due dates so that, for any subset of machines, the set of the time units at which at least one machine is busy, is in interval. We first introduce the notions of pyramidal structure, $k$-hole, $m$-matching, preschedule, $k$-schedule and schedule for this problem. Then we provide a feasibility criteria for a preschedule. The key result of the paper is then to provide a structural necessary and sufficient condition for an instance of the problem to be feasible. We conclude by giving the directions of ongoing works and by bringing open questions related to different variants of the basic non-idling $m$-machine scheduling problem.     

Erratum: Scheduling jobs with position-dependent processing times

Bachman and Janiak provided a sketch of the proof that the problem 1∣r _i ,p _i (v)=a _i /v∣C_max is NP-hard in the strong sense. However, they did not show how to avoid using harmonic numbers whose encoding is not pseudo-polynomial, which makes the proof incomplete. In this corrigendum, we provide a new complete proof.     

Scheduling on parallel identical machines to minimize total tardiness

This paper focuses on the problem of scheduling n independent jobs on m identical parallel machines for the objective of minimizing total tardiness of the jobs. We develop dominance properties and lower bounds, and develop a branch and bound algorithm using these properties and lower bounds as well as upper bounds obtained from a heuristic algorithm. Computational experiments are performed on randomly generated test problems and results show that the algorithm solves problems with moderate sizes in a reasonable amount of computation time.     

Scheduling jobs with release dates and tails on identical machines to minimize the makespan

This paper considers the problem of scheduling independent jobs with release dates and tails on m identical machines to minimize the makespan. This m-machines problem is NP-hard in the strong sense. Jackson's schedule is defined as the list schedule built by giving priority to the available job with the largest tail. It is proved that the deviation of Jackson's schedule from the optimum is smaller than twice the largest processing time.Next, a new branching scheme is proposed by associating with each job an interval of time during which it has to be processed. To branch, the interval for a particular job is divided into two smaller ones. This is a general scheme which can be applied to many scheduling problems.Finally, a branch and bound algorithm is explained in detail and computational results are given.     

Scheduling under a common due-data on parallel unrelated machines

Due-data determination problems have gained significant attention in recent years due to the industrial focus in the just-in-time philosophy. In this paper the problem of scheduling a set of independent jobs on parallel unrelated processors under a common due-date is examined. The common due-date is a decision variable. The objective is to allocate and sequence the jobs on the machines and to determine the optimal due-data, so that the total cost be minimised. This cost is composed of the due-date assignment, the total earliness and the total tardiness cost. As the problem is NP-hard, a polynomial time heuristic procedure, which provides efficient solutions, is developed. The procedure is illustrated by means of an example and is tested via two small size experiments.     

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.