A hybrid genetic algorithm for the multi-depot vehicle routing problem

The distribution of finished products from depots to customers is a practical and challenging problem in logistics management. Better routing and scheduling decisions can result in higher level of customer satisfaction because more customers can be served in a shorter time. The distribution problem is generally formulated as the vehicle routing problem (VRP). Nevertheless, there is a rigid assumption that there is only one depot. In cases, for instance, where a logistics company has more than one depot, the VRP is not suitable. To resolve this limitation, this paper focuses on the VRP with multiple depots, or multi-depot VRP (MDVRP). The MDVRP is NP-hard, which means that an efficient algorithm for solving the problem to optimality is unavailable. To deal with the problem efficiently, two hybrid genetic algorithms (HGAs) are developed in this paper. The major difference between the HGAs is that the initial solutions are generated randomly in HGA1. The Clarke and Wright saving method and the nearest neighbor heuristic are incorporated into HGA2 for the initialization procedure. A computational study is carried out to compare the algorithms with different problem sizes. It is proved that the performance of HGA2 is superior to that of HGA1 in terms of the total delivery time.

Design and development of agent-based procurement system to enhance business intelligence

The purpose of this research is to propose a procurement system across other disciplines and retrieved information with relevant parties so as to have a better co-ordination between supply and demand sides. This paper demonstrates how to analyze the data with an agent-based procurement system (APS) to re-engineer and improve the existing procurement process. The intelligence agents take the responsibility of searching the potential suppliers, negotiation with the short-listed suppliers and evaluating the performance of suppliers based on the selection criteria with mathematical model. Manufacturing firms and trading companies spend more than half of their sales dollar in the purchase of raw material and components. Efficient data collection with high accuracy is one of the key success factors to generate quality procurement which is to purchasing right material at right quality from right suppliers. In general, the enterprises spend a significant amount of resources on data collection and storage, but too little on facilitating data analysis and sharing. To validate the feasibility of the approach, a case study on a manufacturing small and medium-sized enterprise (SME) has been conducted. APS supports the data and information analyzing technique to facilitate the decision making such that the agent can enhance the negotiation and suppler evaluation efficiency by saving time and cost.

Development of an intelligent quality management system using fuzzy association rules

In order to survive in the increasingly customer-oriented marketplace, continuous quality improvement marks the fastest growing quality organization’s success. In recent years, attention has been focused on intelligent systems which have shown great promise in supporting quality control. However, only a small number of the currently used systems are reported to be operating effectively because they are designed to maintain a quality level within the specified process, rather than to focus on cooperation within the production workflow. This paper proposes an intelligent system with a newly designed algorithm and the universal process data exchange standard to overcome the challenges of demanding customers who seek high-quality and low-cost products. The intelligent quality management system is equipped with the ‘‘distributed process mining” feature to provide all levels of employees with the ability to understand the relationships between processes, especially when any aspect of the process is going to degrade or fail. An example of generalized fuzzy association rules are applied in manufacturing sector to demonstrate how the proposed iterative process mining algorithm finds the relationships between distributed process parameters and the presence of quality problems.

Development of a co-operative distributed process mining system for quality assurance

In this paper, a co-operative distributed process mining system (CDPMS) is developed to streamline the workflow along the supply chain in order to offer shorter delivery times, more flexibility and higher customer satisfaction with learning ability. The proposed system is equipped with the ‘distributed process mining’ feature which is used to discover the hidden relationships among each working decision in distributed manner. This method incorporates the concept of data mining and knowledge refinement into decision making process for ensuring ‘doing the right things’ within the workflow. An example of implementation is given, based on the case of slider manufacturer.

Design and development of an agent-based information system for process improvement

To meet changing needs of customers and to survive in the increasingly globalised and competitive environment, it is necessary for companies to equip themselves with intelligent tools, thereby enabling managerial levels to use the tactical decision in a better way. However, the implementation of an intelligent system is always a challenge in Small- and Medium-sized Enterprises (SMEs). Therefore, a new and simple approach with 'process rethinking' ability is proposed to generate ongoing process improvements over time. In this paper, a roadmap of the development of an agent-based information system is described. A case example has also been provided to show how the system can assist non-specialists, for example, managers and engineers to make right decisions for a continual process improvement. Copyright © 2006 Inderscience Enterprises Ltd.

Chemical studies of plasma etchants used in integrated circuit manufacture

Plasma or "dry" etching is an essential process for the production of modern microelectronic circuits. However, despite intensive research, many aspects of the etch process are not fully understood. The results of studies of the plasma etching of Si and Si02 in fluorine-containing discharges, and the complementary technique of plasma polymerisation are presented in this thesis. Optical emission spectroscopy with argon actinometry was used as the principle plasma diagnostic. Statistical experimental design was used to model and compare Si and Si02 etch rates in CF4 and SF6 discharges as a function of flow, pressure and power. Etch mechanisms m both systems, including the potential reduction of Si etch rates in CF4 due to fluorocarbon polymer formation, are discussed. Si etch rates in CF4 /SF6 mixtures were successfully accounted for by the models produced. Si etch rates in CF4/C2F6 and CHF3 as a function of the addition of oxygen-containing additives (02, N20 and CO2) are shown to be consistent with a simple competition between F, 0 and CFx species for Si surface sites. For the range of conditions studied, Si02 etch rates were not dependent on F-atom concentration, but the presence of fluorine was essential in order to achieve significant etch rates. The influence of a wide range of electrode materials on the etch rate of Si and Si02 in CF4 and CF4 /02 plasmas was studied. It was found that the Si etch rate in a CF4 plasma was considerably enhanced, relative to an anodised aluminium electrode, in the presence of soda glass or sodium or potassium "doped" quartz. The effect was even more pronounced in a CF4 /02 discharge. In the latter system lead and copper electrodes also enhanced the Si etch rate. These results could not be accounted for by a corresponding rise in atomic fluorine concentration. Three possible etch enhancement mechanisms are discussed. Fluorocarbon polymer deposition was studied, both because of its relevance to etch mechanisms and its intrinsic interest, as a function of fluorocarbon source gas (CF4, C2F6, C3F8 and CHF3), process time, RF power and percentage hydrogen addition. Gas phase concentrations of F, H and CF2 were measured by optical emission spectroscopy, and the resultant polymer structure determined by X-ray photoelectron spectroscopy and infrared spectroscopy. Thermal and electrical properties were measured also. Hydrogen additions are shown to have a dominant role in determining deposition rate and polymer composition. A qualitative description of the polymer growth mechanism is presented which accounts for both changes in growth rate and structure, and leads to an empirical deposition rate model.

Studies of the effects of molecular encounters on N.M.R. spin-lattice relaxation times

This thesis is concerned with investigations of the effects of molecular encounters on nuclear magnetic resonance spin-lattice relaxation times, with particular reference to mesitylene in mixtures with cyclohexane and TMS. The purpose of the work was to establish the best theoretical description of T1 and assess whether a recently identified mechanism (buffeting), that influences n.m.r. chemical shifts, governs Tl also. A set of experimental conditions are presented that allow reliable measurements of Tl and the N. O. E. for 1H and 13C using both C. W. and F.T. n.m.r. spectroscopy. Literature data for benzene, cyclohexane and chlorobenzene diluted by CC14 and CS2 are used to show that the Hill theory affords the best estimation of their correlation times but appears to be mass dependent. Evaluation of the T1 of the mesitylene protons indicates that a combined Hill-Bloembergen-Purcell-Pound model gives an accurate estimation of T1; subsequently this was shown to be due to cancellation of errors in the calculated intra and intemolecular components. Three experimental methods for the separation of the intra and intermolecular relaxation times are described. The relaxation times of the 13C proton satellite of neat bezene, 1,4 dioxane and mesitylene were measured. Theoretical analyses of the data allow the calculation of Tl intra. Studies of intermolecular NOE's were found to afford a general method of separating observed T1's into their intra and intermolecular components. The aryl 1H and corresponding 13C T1 values and the NOE for the ring carbon of mesitylene in CC14 and C6H12-TMS have been used in combination to determine T1intra and T1inter. The Hill and B.P.P. models are shown to predict similarly inaccurate values for T1linter. A buffeting contribution to T1inter is proposed which when applied to the BPP model and to the Gutowsky-Woessner expression for T1inter gives an inaccuracy of 12% and 6% respectively with respect to theexperimentally based T1inter.

Application of ERS-1 and Topex/Poseidon altimetry using precise orbits

The work described in this thesis concerns the application of radar altimetry, collected from the ERS-1 and TOPEX/POSEIDON missions, to precise satellite orbits computed at Aston University. The data is analysed in a long arc fashion to determine range biases, time tag biases, sea surface topographies and to assess the radial accuracy of the generated orbits through crossover analysis. A sea surface variability study is carried out for the North Sea using repeat altimeter profiles from ERS-1 and TOPEX/POSEIDON in order to verify two local U.K. models for ocean tide and storm surge effects. An on-side technique over the English Channel is performed to compute the ERS-1, TOPEX and POSEIDON altimeter range biases by using a combination of altimetry, precise orbits determined by short arc methods, tide gauge data, GPS measurements, geoid, ocean tide and storm surge models. The remaining part of the thesis presents some techniques for the short arc correction of long arc orbits. Validation of this model is achieved by way of comparison with actual SEASAT short arcs. Simulations are performed for the ERS-1 microwave tracking system, PRARE, using the range data to determine time dependent orbit corrections. Finally, a brief chapter is devoted to the recovery of errors in station coordinates by the use of multiple short arcs.

Teacher relationships:a participative study

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Time-division-multiplexing using pulse position locking for 100 Gb/s applications

Recently, there is a great interest in pushing communication technologies to 100 Gb/s. However, there are still many challenges to perform high speed (> 40 Gb/s) clock and data recovery, and data time-division-multiplexing (TDM). Here, we propose and numerically analyze an asynchronous optical packet retimer using parabolic or sinusoidal phase modulation and linear dispersion. This scheme is named pulse position locking (PPL). Numerical simulation shows that this scheme can effectively resynchronize input signals with arbitrary delays to the local clock, and reduce input jitter. The scheme can also be applied to TDM 10 Gb/s and 40 Gb/s signals to over 100 Gb/s.

Rayleigh noise mitigation in DWDM LR-PONs using carrier suppressed subcarrier-amplitude modulated phase shift keying

We demonstrate a novel Rayleigh interferometric noise mitigation scheme for applications in carrier-distributed dense wavelength division multiplexed (DWDM) passive optical networks at 10 Gbit/s using carrier suppressed subcarrier-amplitude modulated phase shift keying modulation. The required optical signal to Rayleigh noise ratio is reduced by 12 dB, while achieving excellent tolerance to dispersion, subcarrier frequency and drive amplitude variations.

Optical interconnection of core and metro networks

A network concept is introduced that exploits transparent optical grooming of traffic between an access network and a metro core ring network. This network is enabled by an optical router that allows bufferless aggregation of metro network traffic into higher-capacity data streams for core network transmission. A key functionality of the router is WDM to time-division multiplexing (TDM) transmultiplexing.

Graphene based widely-tunable and singly-polarized pulse generation with random fiber lasers

Pulse generation often requires a stabilized cavity and its corresponding mode structure for initial phase-locking. Contrastingly, modeless cavity-free random lasers provide new possibilities for high quantum efficiency lasing that could potentially be widely tunable spectrally and temporally. Pulse generation in random lasers, however, has remained elusive since the discovery of modeless gain lasing. Here we report coherent pulse generation with modeless random lasers based on the unique polarization selectivity and broadband saturable absorption of monolayer graphene. Simultaneous temporal compression of cavity-free pulses are observed with such a polarization modulation, along with a broadly-tunable pulsewidth across two orders of magnitude down to 900 ps, a broadly-tunable repetition rate across three orders of magnitude up to 3 MHz, and a singly-polarized pulse train at 41 dB extinction ratio, about an order of magnitude larger than conventional pulsed fiber lasers. Moreover, our graphene-based pulse formation also demonstrates robust pulse-to-pulse stability and widewavelength operation due to the cavity-less feature. Such a graphene-based architecture not only provides a tunable pulsed random laser for fiber-optic sensing, speckle-free imaging, and laser-material processing, but also a new way for the non-random CW fiber lasers to generate widely tunable and singly-polarized pulses.