A Multi-Objective Optimization for Supply Chain Network Using the Bees Algorithm

A supply chain is a complex network which involves the products, services and information flows between suppliers and customers. A typical supply chain is composed of different levels, hence, there is a need to optimize the supply chain by finding the optimum configuration of the network in order to get a good compromise between the multi-objectives such as cost minimization and lead-time minimization. There are several multi-objective optimization methods which have been applied to find the optimum solutions set based on the Pareto front line. In this study, a swarm-based optimization method, namely, the bees algorithm is proposed in dealing with the multi-objective supply chain model to find the optimum configuration of a given supply chain problem which minimizes the total cost and the total lead-time. The supply chain problem utilized in this study is taken from literature and several experiments have been conducted in order to show the performance of the proposed model; in addition, the results have been compared to those achieved by the ant colony optimization method. The results show that the proposed bees algorithm is able to achieve better Pareto solutions for the supply chain problem

A multi-objective optimisation for supply chain network using the bees algorithm

A supply chain is a complex network which involves the products, services and information flows between suppliers and customers. A typical supply chain is composed of different levels, hence, there is a need to optimize the supply chain by finding the optimum configuration of the network in order to get a good compromise between the multi-objectives such as cost minimization and lead-time minimization. There are several multi-objective optimization methods which have been applied to find the optimum solutions set based on the Pareto front line. In this study, a swarm-based optimization method, namely, the bees algorithm is proposed in dealing with the multi-objective supply chain model to find the optimum configuration of a given supply chain problem which minimizes the total cost and the total lead-time. The supply chain problem utilized in this study is taken from literature and several experiments have been conducted in order to show the performance of the proposed model; in addition, the results have been compared to those achieved by the ant colony optimization method. The results show that the proposed bees algorithm is able to achieve better Pareto solutions for the supply chain problem

Acquisition of Operations Capability: A Model and Test across U.S. and European Firms

In this paper, a three-factor model of operations capability is presented which, unlike previous studies that view capability as an outcome, examines the drivers of capability acquisition. The model proposes that capability acquisition is a function of an organization\u27s commitment to the principles of quality management, just-in-time practices, and effective new product development processes. Furthermore, the paper proposes that these underlying facets of capability acquisition are common across geographic boundaries. The model is tested using data drawn from US and European companies. Results not only provide support for the three-factor model, but also for the invariance of the model and its underlying components between US and European firms

A taxonomic review of supply chain management research

In the previous chapters, we focused largely on quantitative approaches to solving Supply Chain Management (SCM) problems including such issues as: inventory management, supply contracts, information flow, product variety, and international operations. In this chapter, we will broaden our focus to include other approaches t