Product portfolio optimisation using teaching–learning-based optimisation algorithm: a new approach in supply chain management

Abstract

ABSTRACTNowadays, in many industries, there is a possibility to produce a variety of products. In other words, there is an opportunity to produce more than one type of product by using the same available technologies and equipment. Using the portfolio theory, this paper presents a new approach in supply chain management, considering both the perfect and imperfect quality products. The finished goods are considered as a set of multi-products and the aim of the proposed model is to optimise the product portfolio, production rate and supply rate simultaneously. In the proposed method, an advanced optimisation algorithm called ‘teaching–learning-based optimisation (TLBO) algorithm’ is applied for the product portfolio optimisation in a three-layer supply chain. Inspired by the teaching–learning process, the algorithm acts on basis of the effect of influence of a teacher on the output of learners in a class. A numerical example is presented to demonstrate the effectiveness of the proposed algorithm. The results of optimisation using the TLBO algorithm are validated by comparing with particle swarm optimisation algorithm and genetic algorithm.