Collaborative dynamic decision making: a case study from B2B supplier selection

The problem of supplier selection can be easily modeled as a multiple-criteria decision making (MCDM) problem: businesses express their preferences with respect to suppliers, which can then be ranked and selected. This approach has two major pitfalls: first, it does not consider a dynamic scenario, in which suppliers and their ratings are constantly changing; second, it only addressed the problem from the point of view of a single business, and cannot be easily applied when considering more than one business. To overcome these problems, we introduce a method for supplier selection that builds upon the dynamic MCDM framework of Campanella and Ribeiro [1] and, by means of a linear programming model, can be used in the case of multiple collaborating businesses plan- ning their next batch of orders together.Fundação para a Ciência e a Tecnologia, Portugal, under contract CONT DOUT/49/UNINOVA/0/5902/1/200

Key Performance Indicators for Sustainable Campus Assessment: A Case of Andalas University

Sustainable campus has became an important issue amongst universities around the world. Universities can generate a significant impacts to environment due to the high usage of energy, extensive transportation, massive waste, high consumption of materials, and extensive development of buildings and facilities. Thus, there is a need to assess the sustainable campus performance. This paper proposes a set of key performance indicators (KPIs) for sustainable campus assessment consisting of six categories divided into a total of 35 indicators. Analytical Hierarchy Process (AHP) method is applied to determine the importance weight of the KPIs. The results indicated the most important category for the sustainable campus assessment is education with an importance weight of 0.2665, while energy and climate change is regarded as the least important category. It is hoped the proposed KPIs can assist the universities to achieve the higher performance in sustainable campus

Simulation Analysis of a PCB Factory using Factorial Design - A Case Study

This study describes simulation modelling and analysis of a serial production line in a printed circuit board (PCB) factory. Simulation technique is applied to evaluate the performance of the existing manufacturing system, which requires modification to achieve two conflicting objectives, i.e. to maximise the average throughput rate and to minimise the average lead time. Based on a full factorial design, the computer model, which is developed using SIMFACTORY, has been used for finding out the active factors that have a great impact on the current operational problems. Then, a new system design is proposed to enhance the overall performance and is verified using a simulation model. The simulation approach presented here is also applicable to a wide variety of complex operational problems

An AHP model for selection of suppliers in the fast changing fashion market

2010-2011 > Academic research: refereed > Publication in refereed journa

Lot streaming for product assembly in job shop environment

Assembly job shop scheduling problem (AJSP) is an extension of classical job shop scheduling problem (JSP). AJSP starts with JSP and appends an assembly stage to the completed jobs. Lot streaming (LS) technique is a process of splitting jobs into smaller sub-jobs such that successive operations can be overlapped. This paper combines, for the first time, LS and AJSP, extending LS applicability to both machining and assembly. To solve this complex problem, an efficient algorithm is proposed using genetic algorithms and simple dispatching rules. Experimental results suggest that equal size LS outperforms varied size LS with respect to the objective function