Skip to content
naulon
Not checkedNot checked for notices yet.

Complexity analysis of energy-efficient single machine scheduling problems

MohammadMohsen Aghelinejad, Yassine Ouazene, Alice Yalaoui

Operations Research Perspectives · 2019

doi:10.1016/j.orp.2019.100105 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

This paper deals with the complexity analysis of several energy-oriented single-machine scheduling problems addressed in the literature. The considered machine may be in different states: OFF, ON, Idle, or in transitions between them. The energy consumption of the machine at each time-slot is state-dependent. The objective is the minimization of the total energy consumption costs over the planning horizon.For this purpose, two particular cases with constant energy price and increasing energy prices during all the time-slots are studied. These two problems are proved to be polynomial. Moreover, the general version of this problem with Time-Of-Use (TOU) energy prices and different processing times of the jobs is investigated in two versions: with and without the fixed sequence for the jobs. As the results, the version with the fixed sequence is proved to be polynomial, and the version without the fixed sequence (general version) is proved to be NP-hard.This paper also introduces different lower bounds to deal this general version of the problem. The performances of these lower bounds are discussed based on different numerical instances. Keywords: Finite states single-machine scheduling, Energy efficiency, Time of use electricity tariffs, Complexity analysis

Abstract licence: CC BY-NC

References35

    35 more references, whose wording the paper’s licence keeps private.

    Reads

    Read by people on this page

    None yet.

    Checked or read by AI through naulon

    None yet.

    A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

    Are you an author?

    Is this your paper?

    Claim it to add your note and be paid when agents cite it. Free.