Maximising the efficiency of logistics operations with radio frequency identification technology

Radio frequency identification (RFID) technology has gained increasing popularity in businesses to improve operational efficiency and maximise costs saving. However, there is a gap in the literature exploring the enhanced use of RFID to substantially add values to the supply chain operations, especially beyond what the RFID vendors could offer. This paper presents a multi-agent system, incorporating RFID technology, aimed at fulfilling the gap. The system is developed to model supply chain activities (in particular, logistics operations) and is comprised of autonomous and intelligent agents representing the key entities in the supply chain. With the advanced characteristics of RFID incorporated, the agent system examines ways logistics operations (i.e. distribution network) particular) can be efficiently reconfigured and optimised in response to dynamic changes in the market, production and at any stage in the supply chain. © 2012 IEEE.

Controlling the properties of microstructured plastic optical fiber Bragg gratings using acousto-optic excitation

A fine control of the mPOF Bragg grating spectrum properties, such as maximum reflected power and 3dB bandwidth, through acousto-optic modulation (AOM) using flexural regime is presented. A numerical comparison of the strain field along mPOFBG - AOM and the similar structure with SMFBG-AOM was presented, showing that the strain field amplitude is higher along the mPOFBG due to its smaller mechanical stiffness. The obtained results can be used in the development of fine-tuned optical filters using low voltage sources and low frequency regimes, to obtain tunable optical filters and to control the shape of the spectrum. Studies of the behavior in different gratings (such as phase shifted and long period gratings) for photonic applications, such as tunable notch filters or tunable cavities, are in progress. It can potentially be applied on tunable optical filters for POF transmission. © 2012 IEEE.

GIS and optimisation:potential benefits for emergency facility location in humanitarian logistics

Floods are one of the most dangerous and common disasters worldwide, and these disasters are closely linked to the geography of the affected area. As a result, several papers in the academic field of humanitarian logistics have incorporated the use of Geographical Information Systems (GIS) for disaster management. However, most of the contributions in the literature are using these systems for network analysis and display, with just a few papers exploiting the capabilities of GIS to improve planning and preparedness. To show the capabilities of GIS for disaster management, this paper uses raster GIS to analyse potential flooding scenarios and provide input to an optimisation model. The combination is applied to two real-world floods in Mexico to evaluate the value of incorporating GIS for disaster planning. The results provide evidence that including GIS analysis for a decision-making tool in disaster management can improve the outcome of disaster operations by reducing the number of facilities used at risk of flooding. Empirical results imply the importance of the integration of advanced remote sensing images and GIS for future systems in humanitarian logistics.

Advanced predictive-analysis-based decision support for collaborative logistics networks

Purpose – The purpose of this paper is to examine challenges and potential of big data in heterogeneous business networks and relate these to an implemented logistics solution. Design/methodology/approach – The paper establishes an overview of challenges and opportunities of current significance in the area of big data, specifically in the context of transparency and processes in heterogeneous enterprise networks. Within this context, the paper presents how existing components and purpose-driven research were combined for a solution implemented in a nationwide network for less-than-truckload consignments. Findings – Aside from providing an extended overview of today’s big data situation, the findings have shown that technical means and methods available today can comprise a feasible process transparency solution in a large heterogeneous network where legacy practices, reporting lags and incomplete data exist, yet processes are sensitive to inadequate policy changes. Practical implications – The means introduced in the paper were found to be of utility value in improving process efficiency, transparency and planning in logistics networks. The particular system design choices in the presented solution allow an incremental introduction or evolution of resource handling practices, incorporating existing fragmentary, unstructured or tacit knowledge of experienced personnel into the theoretically founded overall concept. Originality/value – The paper extends previous high-level view on the potential of big data, and presents new applied research and development results in a logistics application.

Distributed optimization in transportation and logistics networks

Many important problems in communication networks, transportation networks, and logistics networks are solved by the minimization of cost functions. In general, these can be complex optimization problems involving many variables. However, physicists noted that in a network, a node variable (such as the amount of resources of the nodes) is connected to a set of link variables (such as the flow connecting the node), and similarly each link variable is connected to a number of (usually two) node variables. This enables one to break the problem into local components, often arriving at distributive algorithms to solve the problems. Compared with centralized algorithms, distributed algorithms have the advantages of lower computational complexity, and lower communication overhead. Since they have a faster response to local changes of the environment, they are especially useful for networks with evolving conditions. This review will cover message-passing algorithms in applications such as resource allocation, transportation networks, facility location, traffic routing, and stability of power grids.

Long-term efficacy of orthokeratology contact lens wear in controlling the progression of childhood myopia

Purpose: The primary outcome of this study is to compare the axial length growth of white European myopic children wearing orthokeratology contact lenses (OK) to a control group (CT) over a 7-year period. Methods: Subjects 6–12 years of age with myopia −0.75 to −4.00DS and astigmatism ≤1.00DC were prospectively allocated OK or distance single-vision spectacles (SV) correction. Measurements of axial length (Zeiss IOLMaster), corneal topography, and cycloplegic refraction were taken at 6-month intervals over a 2-year period. Subjects were invited to return to the clinic approximately 5 years later (i.e., 7 years after the beginning of the study) for assessment of their ocular refractive and biometric components. The CT consisted of 4 SV and 12 subjects who switched from SV to soft contact lens wear after the initial 2 years of SV lens wear. Changes in axial length relative to baseline over a 7-year period were compared between groups. Results: Fourteen and 16 subjects from the OK and CT groups, respectively, were examined 6.7 ± 0.5 years after the beginning of the study. Statistically significant changes in the axial length were found over time and between groups (both p <0.001), but not for the time*group interaction (p = 0.125). The change in the axial length for the OK group was 22% (p = 0.328), 42% (p = 0.007), 40% (p = 0.020), 41% (p = 0.013), and 33% (p = 0.062) lower than the CT group following 6, 12, 18, 24, and 84 months of lens wear, respectively. Conclusion: A trend toward a reduction in the rate of axial elongation of the order of 33% was found in the OK group in comparison to the CT group following 7 years of lens wear.