Multi-stage Stochastic Programming Approach for Product Quality Control
Ejiro Stanley Omokoh *
Department of Mathematics, Western Delta University Oghara, Delta State, Nigeria.
Sunday Amaju Ojobor
Department of Mathematics, Delta State University Abraka, Delta State, Nigeria.
Omamoke Enaroseha
Department of Mathematics, Delta State University Abraka, Delta State, Nigeria.
Obed Oyibo
Department of Mathematics, Delta State University of Science and Technology, Delta State, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
This article introduces an innovative stochastic model that addresses a multifaceted supply chain planning challenge involving numerous products, periods, stages, and sites, while also taking into consideration the unpredictability of demand. The intended outcome of employing a two-stage stochastic linear programming methodology is to optimize anticipated return. The analysis encompasses an evaluation of finished and semi-finished product production and inventory levels, backorder quantities, and the quantities of goods that require transportation between upstream and downstream facilities. The resilience of the industrial supply chain plan is subsequently appraised utilizing statistical and risk-based criteria. In this article, a case study from the textile and apparel industry is utilized to illustrate the purpose of this paper: to compare and contrast a deterministic model with a proposed stochastic programming model.
Keywords: Multi-stage, stochastic programming, product, quality control and approach