Scheduling on semi-identical processors

Givenm parallel processors each of them having the same speed but different intervals of availability, the problem of constructing a preemptive schedule forn independent tasks which completes each task in the given intervals is examined. We present an 0 (n+m logm) time algorithm to obtain such a schedule if there exists one. We show that the number of induced preemptions is proportional to the total number of processing intervals of all processors.

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Zusammenfassung Fürm identische Prozessoren, die nur in vorgegebenen Zeitintervallen zur Verfügung stehen, undn unabhängige Verrichtungen wird ein präemptiver Ablaufplan gesucht, so daß alle Verrichtungen innerhalb dieser Intervalle durchgeführt werden können. Es wird gezeigt, daß ein solcher Plan, falls er existiert, mit einem Aufwand von 0 (n + m logm) konstruiert werden kann und die Anzahl der dabei erzeugten Unterbrechungen proportional zur Anzahl der gegebenen Verfügbarkeitsintervalle aller Prozessoren ist.

     

Minimizing the weighted number of tardy jobs on parallel processors

We present a branch-and-bound algorithm to minimize the weighted number of tardy jobs on either identical or non-identical processors. Bounds come from a surrogate relaxation resulting in a multiple-choice knapsack. Extensive computational experiments indicate problems with 400 jobs and several machines can be solved quickly. The results also indicate what parameters affect solution difficulty for this algorithmic approach.     

Scheduling jobs with chain precedence constraints and deteriorating jobs

In this paper we consider a single machine scheduling problem with deteriorating jobs. By deteriorating jobs, we mean that the processing time of a job is a simple linear function of its execution starting time. For the jobs with chain precedence constraints, we prove that the weighted sum of squared completion times minimization problem with strong chains and weak chains can be solved in polynomial time, respectively.     

Scheduling tasks with communication delays on parallel processors

LetP={v ₁,...,v _n } be a set ofn jobs to be executed on a set ofm identical machines. In many instances of scheduling problems, if a jobv _i has to be executed before the jobv _j and both jobs are to be executed on different machines, some sort of information exchange has to take place between the machines executing them. The time it takes for this exchange of information is called a communication delay.In this paper we give anO(n) algorithm to find an optimal scheduling with communication delays when the number of machines is not limited and the precedence constraints on the jobs form a tree.     

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.     

Power-aware scheduling of preemptable jobs on identical parallel processors to minimize makespan

This paper deals with power-aware scheduling of preemptable jobs on identical parallel processors to minimize schedule length when jobs are described by continuous, strictly concave functions relating their processing speed at time t to the amount of power allotted at the moment. Power is a continuous, doubly constrained resource, i.e. both: its availability at time t and consumption over scheduling horizon are constrained. Precedence constraints among jobs are represented by a task-on-arc graph. A methodology based on properties of optimal schedules is presented for solving the problem optimally for a given ordering of nodes in the graph. Heuristics for finding an ordering which leads to possibly short schedules are proposed and examined experimentally.     

Power-aware scheduling of preemptable jobs on identical parallel processors to meet deadlines

This paper deals with a power-aware scheduling of preemptable independent jobs on identical parallel processors where ready time for each job is given and its completion time has to meet a given deadline. Jobs are described by (different) continuous, strictly concave functions relating their processing speeds at a time to the amount of power allotted at the moment. Power is a continuous, doubly constrained resource, i.e. both: its availability at each time instant and consumption over scheduling horizon are constrained. A methodology based on properties of minimum-length schedules is utilized to determine the existence of a feasible schedule for given amounts of energy and power. The question about minimum levels of power and energy ensuring the existence of a feasible schedule for a given set of jobs is also studied.     

Scheduling jobs under an aging effect

In this paper a scheduling problem that takes into consideration a phenomenoncalled ‘aging effect’ with reference to Computer Numerical Controldrilling or cutting machines is investigated. In the aftermath of this effect anexecution of jobs leads to a deterioration of a machine; thus processing timesof jobs increase and the production facility becomes less efficient. However, itis highly desirable to minimize the negative influence of this effect. Ingeneral, it can be done by formulating such a problem in the scheduling contextand optimizing an order of jobs to minimize the given criterion. Therefore, onthis basis a makespan minimization problem on a single machine with releasedates and the aging effect is formulated, where the job processing times aredescribed by non-decreasing functions dependent on fatigue (wear) of machine. Itis proved that even the special cases of the problem are NP-hard. Moreover, someproblems equivalences are shown and polynomially solvable cases are alsoprovided.     

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 time-dependent jobs under mixed deterioration

We consider a new model of time-dependent scheduling. A set of deteriorating jobs has to be processed on a single machine which is available starting from a non-zero time. The processing times of some jobs from this set are constant, while other ones are either proportional or linear functions of the job starting times. The applied criteria of schedule optimality include the maximum completion time, the total completion time, the total weighted completion time, the maximum lateness and the number of tardy jobs. We delineate a sharp boundary between computationally easy and difficult problems, showing polynomially solvable and NP-hard cases.     

Scheduling coupled-operation jobs with exact time-lags

Scheduling coupled-operation jobs with exact time-lags on a single machine has a wide range of applications. In that problem, each job consists of two operations with given processing times, which should be scheduled on a single machine observing a given time-lag. The general case of the problem with arbitrary processing times of operations and arbitrary time lags is known to be NP-hard in the strong sense and the problem remains NP-hard for many special cases. In order to develop a local search algorithm for the problem, we first explore two possible approaches for representing feasible solutions and their neighborhoods based on maintaining a permutation of first operations of the jobs or maintaining a full permutation of all operations. The first representation appears to be unpromising since, as we prove, the problem of finding an optimal sequence of second operations for a fixed sequence of first operations is NP-hard in the strong sense even in the case of unit processing times. We elaborate the second approach by developing a tabu search heuristic based on efficient job re-insertion. Empirical evaluation demonstrates superiority of the developed algorithm in comparison with the earlier published algorithms.     

Scheduling linear deteriorating jobs to minimize the number of tardy jobs

In this paper a problem of scheduling a single machine under linear deterioration which aims at minimizing the number of tardy jobs is considered. According to our assumption, processing time of each job is dependent on its starting time based on a linear function where all the jobs have the same deterioration rate. It is proved that the problem is NP-hard; hence a branch and bound procedure and a heuristic algorithm with O(n ²) is proposed where the heuristic one is utilized for obtaining the upper bound of the B&B procedure. Computational results for 1,800 sample problems demonstrate that the B&B method can solve problems with 28 jobs quickly and in some other groups larger problems are also solved. Generally, B&B method can optimally solve 85% of the samples which shows high performance of the proposed method. Also it is shown that the average value of the ratio of optimal solution to the heuristic algorithm result with the objective ??(1 ? Ui) is at most 1.11 which is more efficient in comparison to other proposed algorithms in related studies in the literature.     

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 unit-length jobs with machine eligibility restrictions

We consider uniform parallel machine scheduling problems with unit-length jobs where every job is only allowed to be processed on a specified subset of machines. We develop efficient methods to solve problems with various objectives, including minimizing a total tardiness function, a maximum tardiness function, total completion time, the number of tardy jobs, the makespan, etc.     

Scheduling with deteriorating jobs and learning effects

This paper studies a single machine scheduling problem simultaneously with deteriorating jobs and learning effects. The objectives are to minimize the makespan and the number of tardy jobs, respectively. Two polynomial time algorithms are proposed to solve these problems optimally.     

Optimal control of assignment of jobs to processors under heavy traffic

The paper is concerned with the optimal control of the assignment of jobs from several arriving random streams to one of a bank of processors. Owing to the difficulty of the general problem, a heavy traffic approach is used. The required work depends on the processor to which it is assigned. The information that the assignment can be based on is quite flexible, and several information structures (data on which the control is based) are considered. The assignment can be made on arrival or when the job is to be processed. There can be bursty arrivals (the bursts depending on randomly varying environmental factors), rather general nonlinear cost functions and other complications. It is shown, under reasonably general conditions, that the optimal costs for the physical systems converge to the optimal cost for the heavy traffic limit problem, as the heavy traffic parameter goes to its limit. Numerical data is presented to illustrate some of the potential uses of the limit process for obtaining optimal contros, or controls satisfying optimal tradeoffs among competing criteria. The methods of proof are quite powerful tools for such optimal control problems     

Scheduling tasks on two processors with deadlines and additional resources

The deterministic scheduling model studied in this paper involves a finite set of identical processors, a finite set of additional resources and a finite set of tasks to be executed, each requiring one processor and specified amounts of additional resources during a known amount of time. Each task is to be completed before its deadline. We establish the complexity status of the two major open nonpreemptive scheduling problems of this type. That is, we prove NP-hardness of two scheduling problems with two processors and unit processing times of all the tasks; the first one has one resource type available in a specified amount, the second one has an arbitrary number of resourcers, each available in amount of one unit. These results are complementary to a previous paper by the first author, where a polynomial-time algorithm was presented for an arbitrary number of processors, one resource type and zero-one resource requirements of the tasks. In addition, in the present paper new restricted versions of One-in-three 3 Sat are also proved to be NP-hard. These heavily restricted versions promise to be useful in other NP-hardness proofs.     

Scheduling jobs with truncated exponential learning functions

In this paper we consider the single machine scheduling problem with truncated exponential learning functions. By the truncated exponential learning functions, we mean that the actual job processing time is a function which depends not only on the total normal processing times of the jobs already processed but also on a control parameter. The use of the truncated function is to model the phenomenon that the learning of a human activity is limited. We show that even with the introduction of the proposed model to job processing times, several single machine problems remain polynomially solvable. For the following three objective functions, the total weighted completion time, the discounted total weighted completion time, the maximum lateness, we present heuristic algorithms according to the corresponding problems without truncated exponential learning functions. We also analyse the worst-case bound of our heuristic algorithms.     

Scheduling multiprocessor tasks on a dynamic configuration of dedicated processors

In the classical scheduling theory, it is widely assumed that a task can be processed by only one processor at a time. With the rapid development of technology, this assumption is no longer valid. In this work we present a problem of scheduling tasks, each of which requires for its processing a set of processors simultaneously and which can be executed on several alternative sets of processors. Scheduling algorithms based on dynamic and linear programming are presented that construct minimum length non-preemptive and preemptive schedules, respectively. Results of computational experiments are also reported.This research was partially supported by a KBN grant and by project CRIT.