Open AccessResource dependent scheduling with truncated learning effects
Author(s) -
Xuyin Wang,
Weiguo Liu,
Lü Li,
Peizhen Zhao,
Ruifeng Zhang
Publication year - 2022
Publication title -
mathematical biosciences and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2022278
Subject(s) - mathematical optimization , scheduling (production processes) , computer science , resource consumption , job shop scheduling , learning effect , single machine scheduling , sequence (biology) , operations research , mathematics , schedule , economics , microeconomics , ecology , biology , operating system , genetics
In this article, we investigate the single-machine scheduling problem with truncated learning effect and resource allocation, where the actual processing time of a job is a general function of its additional resources and position in a sequence. The goal is to determine the optimal resource allocation and optimal sequence such that a weighted sum of scheduling cost and resource consumption cost is minimized. We show that the problem can be solved in $ O(n^3) $ time by using an assignment formulation, where $ n $ is the number of jobs.