Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

An integrated methodology for a sustainable two-stage supplier selection and order allocation problem

Mohammed, Ahmed, Setchi, Rossitza ORCID:, Filip, Misha, Harris, Irina ORCID: and Li, Xiadong 2018. An integrated methodology for a sustainable two-stage supplier selection and order allocation problem. Journal of Cleaner Production 192 , pp. 99-114. 10.1016/j.jclepro.2018.04.131

[thumbnail of 1-s2.0-S0959652618311582-main.pdf]
PDF - Accepted Post-Print Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (815kB) | Preview


Sup­plier se­lec­tion and or­der al­lo­ca­tion are two of the most im­por­tant stages in sup­ply chain man­age­ment. In re­cent years, these de­ci­sions have be­come ma­jor chal­lenges since it has been in­creas­ingly im­por­tant to con­sider the sus­tain­abil­ity of the sup­ply chain. This re­search pre­sents an in­te­grated method­ol­ogy to solve a sus­tain­able two-stage sup­plier se­lec­tion and or­der al­lo­ca­tion prob­lem for a meat sup­ply chain, con­sid­er­ing eco­nomic, en­vi­ron­men­tal and so­cial cri­te­ria. The pro­posed in­te­grated method­ol­ogy in­cludes four phases: (1) the fuzzy an­a­lyt­i­cal hi­er­ar­chy process (AHP) was used to as­sign the rel­a­tive weights for sus­tain­able cri­te­ria; (2) the fuzzy tech­nique for or­der of pref­er­ence by sim­i­lar­ity to ideal so­lu­tion (TOP­SIS) was used to rate sup­pli­ers vis-à-vis their sus­tain­able per­for­mance; (3) a multi-ob­jec­tive pro­gram­ming model (MOPM) was for­mu­lated to ob­tain the op­ti­mal or­der al­lo­ca­tions of quan­tity in or­der to min­imise the costs of trans­porta­tion, pur­chas­ing and ad­min­is­tra­tion, as well as en­vi­ron­men­tal im­pact (par­tic­u­larly CO2 emis­sions) and the travel time of prod­ucts, while max­imis­ing so­cial im­pact and to­tal pur­chas­ing value; and (4) TOP­SIS was used to re­veal the fi­nal so­lu­tion in a set of Pareto so­lu­tions. In in­dus­try, many pa­ra­me­ters are not known pre­cisely. There­fore, the MOPM was re­for­mu­lated into a fuzzy MOPM (FMOPM) to han­dle un­cer­tainty. Af­ter­ward, the ε-con­straint method and LP-met­rics method were em­ployed to op­ti­mise the de­vel­oped FMOPM in terms of ob­tain­ing Pareto so­lu­tions. Fi­nally, a case study was im­ple­mented to ex­am­ine the ap­plic­a­bil­ity of the pro­posed method­ol­ogy.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Business (Including Economics)
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Publisher: Elsevier
ISSN: 0959-6526
Funders: ASTUTE 2020
Date of First Compliant Deposit: 2 May 2018
Date of Acceptance: 15 April 2018
Last Modified: 07 Nov 2023 23:14

Citation Data

Cited 88 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics