Universiti Teknologi Malaysia

About: Universiti Teknologi Malaysia is a education organization based out in Johor Bahru, Malaysia. It is known for research contribution in the topics: Membrane & Control theory. The organization has 21644 authors who have published 39500 publications receiving 520635 citations.

Sustainable supplier selection and order lot-sizing: an integrated multi-objective decision-making process

Abstract: Within supply chains activities, selecting appropriate suppliers based on the sustainability criteria (economic, environmental and social) can help companies move toward sustainable development. Although several studies have recently been accomplished to incorporate sustainability criteria into supplier selection problem, much less attention has been devoted to developing a comprehensive mathematical model that allocates the optimal quantities of orders to suppliers considering lot-sizing problems. In this research, we propose an integrated approach of rule-based weighted fuzzy method, fuzzy analytical hierarchy process and multi-objective mathematical programming for sustainable supplier selection and order allocation combined with multi-period multi-product lot-sizing problem. The mathematical programming model consists of four objective functions which are minimising total cost, maximising total social score, maximising total environmental score and maximising total economic qualitative score. The prop...

Blasting-induced flyrock and ground vibration prediction through an expert artificial neural network based on particle swarm optimization

Abstract: Blasting is a major component of the construction and mining industries in terms of rock fragmentation and concrete demolition. Blast designers are constantly concerned about flyrock and ground vibration induced by blasting as adverse and unintended effects of explosive usage on the surrounding areas. In recent years, several researches have been done to predict flyrock and ground vibration by means of conventional backpropagation (BP) artificial neural network (ANN). However, the convergence rate of the BP-ANN is relatively slow and solutions can be trapped at local minima. Since particle swarm optimization (PSO) is a robust global search algorithm, it can be used to improve ANNs' performance. In this study, a novel approach of incorporating PSO algorithm with ANN has been proposed to eliminate the limitation of the BP-ANN. This approach was applied to simulate the flyrock distance and peak particle velocity (PPV) induced by blasting. PSO parameters and optimal network architecture were determined using sensitivity analysis and trial and error method, respectively. Finally, a model was selected, and the proposed model was trained and tested using 44 datasets obtained from three granite quarry sites in Malaysia. Each dataset involved ten inputs, including the most influential parameters on flyrock distance and PPV, and two outputs. The results indicate that the proposed method is able to predict flyrock distance and PPV induced by blasting with a high degree of accuracy. Sensitivity analysis was also conducted to determine the influence of each parameter on flyrock distance and PPV. The results show that the powder factor and charge per delay are the most effective parameters on flyrock distance, whereas sub-drilling and charge per delay are the most effective parameters on PPV.

Development of key performance measures for the automobile green supply chain

Abstract: The main purpose of this study was to develop a set of measures for evaluating the performance of the automobile green supply chain This study reviewed various literatures on green supply chain performance measurement, environmental management, traditional supply chain performance measurement, and automobile supply chain management In order to comprehensively and effectively establish the relevant measures, a suitable framework which considered the automobile green supply chain as a two-in-one chain was adopted This two-in-one chain comprised a forward and backward chain for the automobile industry Consequently, 10 measures with 49 metrics and 6 measures with 23 metrics were identified and developed for the forward and backward chains, respectively Sequel to the development of these measures, a survey was conducted using a four-page questionnaire distributed to experts (including academics and practitioners) to establish their importance and applicability The findings of this study suggested that the importance and applicability of all the developed measures have been substantiated For the forward chain, the most crucial measure was customer perspective while the most applicable one was traditional supply chain cost The reverse chain measures were topped by management commitment in terms of both importance and applicability This study contributed to the advancement of knowledge by pioneering the development of a set of holistic measures for evaluating the performance of the automobile green supply chain The study was wrapped up with the proposition of directions for further studies