A joint supplier selection and lot-sizing problem considering quality constraint and quantity discount

Xin Li, Jose A. Ventura, M. Jeya Chandra

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

This paper considers a joint supplier selection and lot-sizing problem, where suppliers are capacitated and offer a certain type of quantity discount. The product's perfect rate varies among suppliers and a minimum average acceptable perfect rate (APR) is required. Besides, in order to facilitate production plans, orders placed to suppliers are required to cover the demand corresponding to an interval that is multiple of a given time unit. A cyclic order schedule is employed, and the set of selected suppliers and corresponding order quantities and frequencies are determined accordingly so that the total cost per time unit (CPT) is minimized. A mixed-integer linear programming model is presented. An exact algorithm based on dynamic programming (DPA) is proposed. A numerical example is presented to illustrate the application of the model and algorithm. DPA not only solves the problem optimally but also provides the trade-off between CPT and APR for the decision maker.

Original languageEnglish (US)
Title of host publication67th Annual Conference and Expo of the Institute of Industrial Engineers 2017
EditorsHarriet B. Nembhard, Katie Coperich, Elizabeth Cudney
PublisherInstitute of Industrial Engineers
Pages325-330
Number of pages6
ISBN (Electronic)9780983762461
StatePublished - 2017
Event67th Annual Conference and Expo of the Institute of Industrial Engineers 2017 - Pittsburgh, United States
Duration: May 20 2017May 23 2017

Publication series

Name67th Annual Conference and Expo of the Institute of Industrial Engineers 2017

Other

Other67th Annual Conference and Expo of the Institute of Industrial Engineers 2017
Country/TerritoryUnited States
CityPittsburgh
Period5/20/175/23/17

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

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