Supplier selection and order allocation using a stochastic multi-objective programming model and genetic algorithm
by Hadi Moheb-Alizadeh; Morteza Mahmoudi; Rouhallah Bagheri
International Journal of Integrated Supply Management (IJISM), Vol. 11, No. 4, 2017

Abstract: In this paper, we develop a supplier selection and order allocation multi-objective model in stochastic environment in which purchasing cost, percentage of delivered items with delay and percentage of rejected items provided by each supplier are supposed to be stochastic parameters following any arbitrary probability density function. To do so, we use dependent chance programming (DCP) that maximises probability of the event that total purchasing cost, total delivered items with delay and total rejected items are less than or equal to pre-determined values given by decision maker. After transforming the abovementioned stochastic multi-objective programming problem into a stochastic single objective problem using minimum deviation method, we apply a genetic algorithm to solve the later single objective problem. The employed genetic algorithm performs a simulation process in order to calculate the stochastic objective function as its fitness function. A stochastic analysis reveals that incorporation of stochasticity into the supplier selection and order allocation problem will be advantageous for a purchasing firm with respect to purchasing cost, percentage of delivered items with delay and percentage of rejected items. Furthermore, we explore the impact of stochastic parameters on the given solution via a sensitivity analysis exploiting coefficient of variation. The results show that as stochastic parameters have greater coefficients of variation, the value of objective function in the stochastic single objective programming problem is worsened.

Online publication date: Tue, 13-Feb-2018

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Integrated Supply Management (IJISM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com