Integrated dynamic vendor selection and order allocation problem for the time dependent and stochastic data

• Published in: Benchmarking : an international journal Vol. 25; no. 3; pp. 777 - 796
• Main Authors: Aggarwal, Remica, Singh, Surya Prakash, Kapur, P.K
• Format: Journal Article
• Language: English
• Published: Bradford Emerald Publishing Limited 03.04.2018; Emerald Group Publishing Limited
• Subjects: Algorithms; Costs; Data envelopment analysis; Design optimization; Discounts; Goal programming; Inventory; Inventory control; Lead time; Multiple objective analysis; Operations management; Optimization; Order quantity; Purchasing; Studies; Suppliers; Supply chains; Time dependence; Uncertainty; Stochastic model; Vendor selection; Goal programming
• ISSN: 1463-5771; 1758-4094
• DOI: 10.1108/BIJ-05-2017-0085

Purpose In this paper, vendor selection and order allocation problem is considered for a buyer dealing in multiple products to be supplied by multiple vendors. Each product has an associated lead time with stochastic demand having stochastic capacity for each vendor across entire time period. Uncertainties related to costs which are further influenced by the periodically changing incremental quantity discounts offered by various vendors. The purpose of this paper is to find an optimal trade-off of vendor selection and order allocation in the presence of uncertainties involving multiple conflicting objectives such as cost minimization, service level/quality level maximization and delivery lead time minimization concurrently. Design/methodology/approach Vendor selection problem considered here has a multi-objective optimization design subject to a set of demand, capacity and quantity discount based constraints. These constraints as well as uncertainty related to lead time have been handled using chance constraint approach. The problem is titled as “integrated dynamic vendor selection problem (IDVSP).” The proposed multi-objective IDVSP is solved using both non-pre-emptive goal programming (GP) and weighted sum aggregate objective function (AOF) technique. Findings Findings indicate goal achievement for different objectives from both non-pre-emptive GP and AOF procedure. While the goals are satisfactorily achieved as per the target values for cost and lead time, quality/service level was somewhat compromised in order to find an appropriate trade off. Originality/value The research work is original as it integrates dynamic as well as stochastic (uncertain) nature of supply chain simultaneously coupled with the concept of incremental quantity discounts on lot sizes.