Computing lower and upper bounds for a large-scale industrial job shop scheduling problem

Márton Drótos, Gábor Erdos, T. Kis

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

In this paper we present a case study from the lighting industry concerned with the scheduling of a set of job families each representing the production of a particular end-item in a given quantity. It is a job shop type problem, where each job family has a number of routing alternatives, and the solution has to respect batching and machine availability constraints. All jobs of the same job family have a common release date and a common due date, and they differ only in size. The objective is to minimize the total tardiness of the job families, rather than that of individual jobs. We propose a two-phase method based on solving a mixed-integer linear program and then improving the initial solution by tabu search. We evaluate our method on real-world as well as generated instances.

Original languageEnglish
Pages (from-to)296-306
Number of pages11
JournalEuropean Journal of Operational Research
Volume197
Issue number1
DOIs
Publication statusPublished - Aug 16 2009

Fingerprint

Job Shop Scheduling Problem
Upper and Lower Bounds
Tabu search
Computing
Lighting
Scheduling
Availability
Availability Constraints
Common Due Date
Total Tardiness
Release Dates
Batching
Job Shop
Integer Program
Tabu Search
Linear Program
Industry
Routing
Minimise
Family

Keywords

  • Batching
  • Mathematical programming
  • Scheduling
  • Tabu search

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Modelling and Simulation
  • Information Systems and Management

Cite this

Computing lower and upper bounds for a large-scale industrial job shop scheduling problem. / Drótos, Márton; Erdos, Gábor; Kis, T.

In: European Journal of Operational Research, Vol. 197, No. 1, 16.08.2009, p. 296-306.

Research output: Contribution to journalArticle

@article{59501184125343d0a065938552cf0cfc,
title = "Computing lower and upper bounds for a large-scale industrial job shop scheduling problem",
abstract = "In this paper we present a case study from the lighting industry concerned with the scheduling of a set of job families each representing the production of a particular end-item in a given quantity. It is a job shop type problem, where each job family has a number of routing alternatives, and the solution has to respect batching and machine availability constraints. All jobs of the same job family have a common release date and a common due date, and they differ only in size. The objective is to minimize the total tardiness of the job families, rather than that of individual jobs. We propose a two-phase method based on solving a mixed-integer linear program and then improving the initial solution by tabu search. We evaluate our method on real-world as well as generated instances.",
keywords = "Batching, Mathematical programming, Scheduling, Tabu search",
author = "M{\'a}rton Dr{\'o}tos and G{\'a}bor Erdos and T. Kis",
year = "2009",
month = "8",
day = "16",
doi = "10.1016/j.ejor.2008.06.004",
language = "English",
volume = "197",
pages = "296--306",
journal = "European Journal of Operational Research",
issn = "0377-2217",
publisher = "Elsevier",
number = "1",

}

TY - JOUR

T1 - Computing lower and upper bounds for a large-scale industrial job shop scheduling problem

AU - Drótos, Márton

AU - Erdos, Gábor

AU - Kis, T.

PY - 2009/8/16

Y1 - 2009/8/16

N2 - In this paper we present a case study from the lighting industry concerned with the scheduling of a set of job families each representing the production of a particular end-item in a given quantity. It is a job shop type problem, where each job family has a number of routing alternatives, and the solution has to respect batching and machine availability constraints. All jobs of the same job family have a common release date and a common due date, and they differ only in size. The objective is to minimize the total tardiness of the job families, rather than that of individual jobs. We propose a two-phase method based on solving a mixed-integer linear program and then improving the initial solution by tabu search. We evaluate our method on real-world as well as generated instances.

AB - In this paper we present a case study from the lighting industry concerned with the scheduling of a set of job families each representing the production of a particular end-item in a given quantity. It is a job shop type problem, where each job family has a number of routing alternatives, and the solution has to respect batching and machine availability constraints. All jobs of the same job family have a common release date and a common due date, and they differ only in size. The objective is to minimize the total tardiness of the job families, rather than that of individual jobs. We propose a two-phase method based on solving a mixed-integer linear program and then improving the initial solution by tabu search. We evaluate our method on real-world as well as generated instances.

KW - Batching

KW - Mathematical programming

KW - Scheduling

KW - Tabu search

UR - http://www.scopus.com/inward/record.url?scp=59649096254&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=59649096254&partnerID=8YFLogxK

U2 - 10.1016/j.ejor.2008.06.004

DO - 10.1016/j.ejor.2008.06.004

M3 - Article

AN - SCOPUS:59649096254

VL - 197

SP - 296

EP - 306

JO - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

IS - 1

ER -