A multi-criterion approach for Kanban allocations

A. A. Andijani

doi:10.1016/S0305-0483(98)00004-8

A multi-criterion approach for Kanban allocations

A. A. Andijani^*

^*Corresponding author for this work

King Fahd University of Petroleum & Minerals

Research output: Contribution to journal › Article › peer-review

22 Scopus citations

Abstract

In this paper, a single-item, multi-stage, serial production system is considered. Materials in the system are controlled by Kanban discipline. A fixed total number of Kanbans over a given number of serial workstations is allocated. Three conflicting objectives, the average throughput rate (to be maximized), the average work-in-process (to be minimized), and the average flow time (to be minimized) are considered. Stochastic system simulation is used to generate the efficient set of Kanban allocations. Then the analytic hierarchy process (AHP) is utilized to identify the most-preferred allocation. An illustrative example is given.

Original language	English
Pages (from-to)	483-493
Number of pages	11
Journal	Omega
Volume	26
Issue number	4
DOIs	https://doi.org/10.1016/S0305-0483(98)00004-8
State	Published - Aug 1998

Bibliographical note

Funding Information:
The author gratefully acknowledges the support of the King Fahd University of Petroleum and Minerals.

Keywords

AHP
Kanban allocations
MCDM
Serial production systems
Stochastic simulation

ASJC Scopus subject areas

Strategy and Management
Management Science and Operations Research
Information Systems and Management

Access to Document

10.1016/S0305-0483(98)00004-8

Cite this

@article{a12f86b6462a4ef6b0241d8c704931d3,

title = "A multi-criterion approach for Kanban allocations",

abstract = "In this paper, a single-item, multi-stage, serial production system is considered. Materials in the system are controlled by Kanban discipline. A fixed total number of Kanbans over a given number of serial workstations is allocated. Three conflicting objectives, the average throughput rate (to be maximized), the average work-in-process (to be minimized), and the average flow time (to be minimized) are considered. Stochastic system simulation is used to generate the efficient set of Kanban allocations. Then the analytic hierarchy process (AHP) is utilized to identify the most-preferred allocation. An illustrative example is given.",

keywords = "AHP, Kanban allocations, MCDM, Serial production systems, Stochastic simulation",

author = "Andijani, \{A. A.\}",

note = "Funding Information: The author gratefully acknowledges the support of the King Fahd University of Petroleum and Minerals.",

year = "1998",

month = aug,

doi = "10.1016/S0305-0483(98)00004-8",

language = "English",

volume = "26",

pages = "483--493",

journal = "Omega",

issn = "0305-0483",

publisher = "Elsevier B.V.",

number = "4",

}

TY - JOUR

T1 - A multi-criterion approach for Kanban allocations

AU - Andijani, A. A.

N1 - Funding Information: The author gratefully acknowledges the support of the King Fahd University of Petroleum and Minerals.

PY - 1998/8

Y1 - 1998/8

N2 - In this paper, a single-item, multi-stage, serial production system is considered. Materials in the system are controlled by Kanban discipline. A fixed total number of Kanbans over a given number of serial workstations is allocated. Three conflicting objectives, the average throughput rate (to be maximized), the average work-in-process (to be minimized), and the average flow time (to be minimized) are considered. Stochastic system simulation is used to generate the efficient set of Kanban allocations. Then the analytic hierarchy process (AHP) is utilized to identify the most-preferred allocation. An illustrative example is given.

AB - In this paper, a single-item, multi-stage, serial production system is considered. Materials in the system are controlled by Kanban discipline. A fixed total number of Kanbans over a given number of serial workstations is allocated. Three conflicting objectives, the average throughput rate (to be maximized), the average work-in-process (to be minimized), and the average flow time (to be minimized) are considered. Stochastic system simulation is used to generate the efficient set of Kanban allocations. Then the analytic hierarchy process (AHP) is utilized to identify the most-preferred allocation. An illustrative example is given.

KW - AHP

KW - Kanban allocations

KW - MCDM

KW - Serial production systems

KW - Stochastic simulation

UR - https://www.scopus.com/pages/publications/0032135154

U2 - 10.1016/S0305-0483(98)00004-8

DO - 10.1016/S0305-0483(98)00004-8

M3 - Article

AN - SCOPUS:0032135154

SN - 0305-0483

VL - 26

SP - 483

EP - 493

JO - Omega

JF - Omega

IS - 4

ER -

A multi-criterion approach for Kanban allocations

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this