A classification of dynamic programming formulations for offline deterministic single-machine scheduling problems

•We focus on single-machine scheduling problems.•We review dynamic programming formulations.•We categorize these formulations We review dynamic programming (DP) algorithms utilized to solve offline deterministic single-machine scheduling problems. We classify DP algorithms based on problem propertie...

Full description

Saved in:
Bibliographic Details
Published in:European journal of operational research Vol. 305; no. 3; pp. 999 - 1017
Main Authors: Koulamas, Christos, Kyparisis, George J.
Format: Journal Article
Language:English
Published: Elsevier B.V 01.03.2023
Subjects:
Dynamic programming
Scheduling
Single-machine
Single-machine
Scheduling
Dynamic programming
ISSN:0377-2217, 1872-6860
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:•We focus on single-machine scheduling problems.•We review dynamic programming formulations.•We categorize these formulations We review dynamic programming (DP) algorithms utilized to solve offline deterministic single-machine scheduling problems. We classify DP algorithms based on problem properties and provide insights on how these properties facilitate the use of specific types of DP algorithms. These properties center on whether jobs in a schedule can be naturally partitioned into subsets or whether a complete schedule is the outcome of blending distinct subsequences and/or whether the overall scheduling objective is a compromise of conflicting objectives. We propose generalizations of existing DP algorithms so they can be applied to more general problems such as proportionate flow shops. In some cases, we show how the running time of a DP algorithm can be improved. We also survey models where a DP formulation is part of a hybrid enumerative algorithm. A discussion on how pseudo-polynomial DP algorithms can be converted to fully polynomial time approximation schemes is also presented. We conclude our review with a timeline of DP algorithmic development during the last 50 years.
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2022.03.043