Enhancing network transmission capacity by efficiently allocating node capability

A network s transmission capacity is the maximal rate of traffic inflow that the network can handle without causing congestion Here we study how to enhance this quantity by allocating resource to individual nodes while preserving the total amount of the resource available We propose a practical and effective scheme which redistributes node capability based on the local knowledge of node connectivity We show that our scheme enhances the transmission capacity of networks with heterogeneous structures by up to two orders of magnitude

A mixed integer programming model to evaluate the impact of business factors on global manufacturing relocation decisions

In recent years, dramatic changes in business factors have triggered a trend of manufacturing relocation out of 'The World's Factory', which is the Pearl River Delta (PRO), China. Global manufacturers in PRO have been facing unprecedented operating cost pressure, due to RI1B currency appreciation, rising labor cost, highly volatile oil price, tax rebate adjustment and industry policy changes. This paper presents a Mixed Integer Programming (MIP) model, to evaluate the impact of business factors on global manufacturing relocation decisions. Objective function of the MIP model is to minimize Total Landed Cost (TLC) for international markets. Application of the MIP model is illustrated through a case study with a hypothetical footwear manufacturer. Managerial implications on supply chain dynamics and regional economy are derived from modeling results and analysis.published_or_final_versio

Tourism supply chain management : a new research agenda

2008-2009 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Risk assessment using transfer learning for grassland fires

© 2019 A new direction of risk assessment research in grassland fire management is data-driven prediction, in which data are collected from particular regions. Since some regions have rich datasets that can easily generate knowledge for risk prediction, and some have no data available, this study addresses how we can leverage the knowledge learned from one grassland risk assessment to assist with a current assessment task. In this paper, we first introduce the transfer learning methodology to map and update risk maps in grassland fire management, and we propose a new grassland fire risk analysis method. In this study, two major grassland areas (Xilingol and Hulunbuir) in northern China are selected as the study areas, and five representative indicators (features) are extracted from grassland fuel, fire climate, accessibility, human and social economy. Taking Xilingol as the source domain (where sufficient labelled data are available) and Hulunbuir as the target domain (which contains insufficient data but requires risk assessment/prediction), we then establish the mapping relationship between grassland fire indicators and the degrees of grassland fire risk by using a transfer learning method. Finally, the fire risk in the Hulunbuir grassland is assessed using the transfer learning method. Experiments show that the prediction accuracy reached 87.5% by using the transfer learning method, representing a significant increase over existing methods

RFID-enabled complex event processing application framework for manufacturing

In order to face up with classic manufacturing challenges such as high work in progress (WIP) inventories, complexity in production planning and scheduling, and low labour and machine utilisation, many manufacturing companies made their efforts in implementing RFID (Radio Frequency Identification Devices) throughout the manufacturing workshops. Through this way, all production data in manufacturing fields can be obtained in real time, and it improves the flexibility and responsivity to the changing market for the companies. However, at the same time the RFID deployment also introduces a new challenge which requires an effective and efficient method to handle the large amounts of events. This paper proposes an application framework for a real-time Complex Event Management System (CEMS) based on RFID equipments deployment. With the use of Complex Event Processing (CEP) technologies, this system allows users to obtain interested and meaningful information from large numbers of primitive events captured from the RFID devices deployed in manufacturing shop-floor in real time. This paper presents the RFID deployment infrastructure first, and then system design of the CEMS is proposed. © 2011 Inderscience Enterprises Ltd.postprin

An integrated pricing and deteriorating model and a hybrid algorithm for a VMI (vendor-managed-inventory) supply chain

This paper studies a vendor-managed-inventory (VMI) supply chain where a manufacturer, as a vendor, procures a type of nondeteriorating raw material to produce a deteriorating product, and distribute it to multiple retailers. The price of the product offered by one retailer is also influenced by the prices offered by other retailers because consumers can choose the product from any of the retailers. This paper is one of the first papers that propose an integrated model to study the influence of pricing and deterioration on the profit of such a VMI system. A hybrid approach combining genetic algorithms and an analytical method is developed for efficiently determining the optimal price of the product of each retailer, the inventory policies of the product and the raw material. Our results of a detailed numerical study show that parameters related to the market and deterioration have significant influences on the profit of the VMI system. However, different from common intuition, we find that an increase in the substitution elasticity of the product among different retailers can bring an increase in the retail prices of the product, while the increase of the market scale can reduce the retail prices. © 2011 IEEE.published_or_final_versio

The further study on the accuracy of DEM terrain representation

2003-2004 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Guest editorial: digital enterprise technology

published_or_final_versionSpringer Open Choice, 21 Feb 201

An algorithm for solving rule sets-based bilevel decision problems

Bilevel decision addresses the problem in which two levels of decision makers each tries to optimize their individual objectives under certain constraints, and to act and react in an uncooperative and sequential manner. Given the difficulty of formulating a bilevel decision problem by mathematical functions, a rule sets-based bilevel decision (RSBLD) model was proposed. This article presents an algorithm to solve a RSBLD problem. A case-based example is given to illustrate the functions of the proposed algorithm. Finally, a set of experiments is analyzed to further show the functions and the effectiveness of the proposed algorithm. © 2011 Wiley Periodicals, Inc