Abstract

We consider a variant of the NP-hard problem of assigning jobs to machines to minimize the completion time of the last job. Usually, precedence constraints are given by a partial order on the set of jobs, and each job requires all its predecessors to be completed before it can start. In this paper, we consider a different type of precedence relation that has not been discussed as extensively and is called OR-precedence. In order for a job to start, we require that at least one of its predecessors is completed—in contrast to all its predecessors. Additionally, we assume that each job has a release date before which it must not start. We prove that a simple List Scheduling algorithm due to Graham (Bell Syst Tech J 45(9):1563–1581, 1966) has an approximation guarantee of 2 and show that obtaining an approximation factor of 4/3 - varepsilon is NP-hard. Further, we present a polynomial-time algorithm that solves the problem to optimality if preemptions are allowed. The latter result is in contrast to classical precedence constraints where the preemptive variant is already NP-hard. Our algorithm generalizes previous results for unit processing time jobs subject to OR-precedence constraints, but without release dates. The running time of our algorithm is O(n^2) for arbitrary processing times and it can be reduced to O(n) for unit processing times, where n is the number of jobs. The performance guarantees presented here match the best-known ones for special cases where classical precedence constraints and OR-precedence constraints coincide.

Highlights

  • In this paper, we consider the problem of scheduling jobs with OR-precedence constraints on parallel identical machines to minimize the time necessary to complete all jobs

  • We discuss the problem of minimizing the makespan on parallel identical machines with OR-precedence constraints

  • We introduce the concept of minimal chains, and use it to prove that List Scheduling (Graham 1966) achieves an approximation guarantee of 2

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Summary

Introduction

We consider the problem of scheduling jobs with OR-precedence constraints on parallel identical machines to minimize the time necessary to complete all jobs. Depending on the problem definition, jobs are allowed to be preempted at integer points in time (preemptive scheduling) or not at all (non-preemptive scheduling). The. A schedule is called feasible if S j ≥ min{Ci | i ∈ P( j)} and S j ≥ r j for all jobs j ∈ [n]. A job without predecessors may start at any point in time t ≥ r j. The non-preemptive problem is NP-hard, which is why we are interested in Journal of Scheduling (2021) 24:319–328 approximation algorithms. Let Π be a minimization problem, and α ≥ 1. Recall that an α-approximation algorithm for Π is a polynomial-time algorithm that returns a feasible solution with objective value at most α times the optimal objective value

Non-preemptive scheduling
Preemptive scheduling
Main results
Preliminaries and minimal chains
Approximability and hardness for the non-preemptive setting
A polynomial-time algorithm for the preemptive case
Concluding remarks
Full Text
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