Engineering Commons^™

Traffic Simulation Model For Port Planning And Congestion Prevention, Baoxiang Li, Kar Way Tan, Trong Khiem Tran

Research Collection School Of Computing and Information Systems

Effective management of land-side transportation provides the competitive advantage to port terminal operators in improving services and efficient use of limited space in an urban port. We present a hybrid simulation model that combines traffic-flow modeling and discrete-event simulation for land-side port planning and evaluation of traffic conditions for a number of what-if scenarios. We design our model based on a real-world case of a bulk cargo port. The problem is interesting due to complexity of heterogeneous closed-looped internal vehicles and external vehicles traveling in spaces with very limited traffic regulation (no traffic lights, no traffic wardens) and the traffic …

Computer-Aided Design Of Algorithms Of Pulsed Control Of Arc Welding Process Based On Numerical Simulation, Oksana I. Shpigunova, Anatoliy A. Glazunov

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.

Improving Carbon Efficiency Through Container Size Optimization And Shipment Consolidation, Nang Laik Ma, Kar Way Tan, Edwin Lik Ming Chong

Research Collection School Of Computing and Information Systems

Purpose: Many manufacturing companies that ship goods through full container loads found themselves under-utilizing the containers and resulting in higher carbon footprint per volume shipment. One of the reasons is the choice of non-ideal container sizes for their shipments. Consolidation fills up the containers more efficiently that reduces the overall carbon footprint. The objective of this paper is to support decisions on selection of appropriate combination of container sizes and shipment consolidation for a manufacturing company. We develop two-steps model which first takes the volumes to be shipped as an input and provide the combination of container sizes required; then …

Achieving High Reliability And Efficiency In Maintaining Large-Scale Storage Systems Through Optimal Resource Provisioning And Data Placement, Lipeng Wan

Doctoral Dissertations

With the explosive increase in the amount of data being generated by various applications, large-scale distributed and parallel storage systems have become common data storage solutions and been widely deployed and utilized in both industry and academia. While these high performance storage systems significantly accelerate the data storage and retrieval, they also bring some critical issues in system maintenance and management. In this dissertation, I propose three methodologies to address three of these critical issues.

First, I develop an optimal resource management and spare provisioning model to minimize the impact brought by component failures and ensure a highly operational experience …

Self-Organizing Neural Network For Adaptive Operator Selection In Evolutionary Search, Teck Hou Teng, Stephanus Daniel Handoko, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Evolutionary Algorithm is a well-known meta-heuristics paradigm capable of providing high-quality solutions to computationally hard problems. As with the other meta-heuristics, its performance is often attributed to appropriate design choices such as the choice of crossover operators and some other parameters. In this chapter, we propose a continuous state Markov Decision Process model to select crossover operators based on the states during evolutionary search. We propose to find the operator selection policy efficiently using a self-organizing neural network, which is trained offline using randomly selected training samples. The trained neural network is then verified on test instances not used for …

Robust Influence Maximization, Meghna Lowalekar, Pradeep Varakantham, Akshat Kumar

Research Collection School Of Computing and Information Systems

Influence Maximization is the problem of finding a fixed size set of nodes, which will maximize the expected number of influenced nodes in a social network. The number of influenced nodes is dependent on the influence strength of edges that can be very noisy. The noise in the influence strengths can be modeled using a random noise or adversarial noise model. It has been shown that all random processes that independently affect edges of the graph can be absorbed into the activation probabilities themselves and hence random noise can be captured within the independent cascade model. On the other hand, …

Simultaneous Optimization And Sampling Of Agent Trajectories Over A Network, Hala Mostafa, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We study the problem of optimizing the trajectories of agents moving over a network given their preferences over which nodes to visit subject to operational constraints on the network. In our running example, a theme park manager optimizes which attractions to include in a day-pass to maximize the pass’s appeal to visitors while keeping operational costs within budget. The first challenge in this combinatorial optimization problem is that it involves quantities (expected visit frequencies of each attraction) that cannot be expressed analytically, for which we use the Sample Average Approximation. The second challenge is that while sampling is typically done …

Optimal Scheduling Of Pev Charging/Discharging In Microgrids With Combined Objectives, Chong Cao, Ming Cheng, Bo Chen

Michigan Tech Publications

While renewable power generation and vehicle electrification are promising solutions to reduce greenhouse gas emissions, it faces great challenges to effectively integrate them in a power grid. The weather-dependent power generation of renewable energy sources, such as Photovoltaic (PV) arrays, could introduce significant intermittency to a power grid. Meanwhile, uncontrolled PEV charging may cause load surge in a power grid. This paper studies the optimization of PEV charging/discharging scheduling to reduce customer cost and improve grid performance. Optimization algorithms are developed for three cases: 1) minimize cost, 2) minimize power deviation from a pre-defined power profile, and 3) combine objective …

Shortest Path Based Decision Making Using Probabilistic Inference, Akshat Kumar

Research Collection School Of Computing and Information Systems

We present a new perspective on the classical shortest path routing (SPR) problem in graphs. We show that the SPR problem can be recast to that of probabilistic inference in a mixture of simple Bayesian networks. Maximizing the likelihood in this mixture becomes equivalent to solving the SPR problem. We develop the well known Expectation-Maximization (EM) algorithm for the SPR problem that maximizes the likelihood, and show that it does not get stuck in a locally optimal solution. Using the same probabilistic framework, we then address an NP-Hard network design problem where the goal is to repair a network of …

Gravitational Search Algorithm For Determining Controller Parameters In An Automatic Voltage Regulator System, Serhat Duman, Nuran Yörükeren, İsmai̇l Hakki Altaş

Turkish Journal of Electrical Engineering and Computer Sciences

proportional-integral-derivate (PID) controller for an automatic voltage regulator (AVR) system using a heuristic gravitational search algorithm (GSA) based on mass interactions and Newton's law of gravity. The determination of optimal controller parameters is considered an optimization problem in which different performance indexes and a performance criterion in the time domain have been used as objective functions to test the performance and effectiveness of the GSA. In the determining process of the parameters, the designed PID controller with the proposed approach is simulated under different conditions and the performance of the controller is compared with those reported in the literature. From …

Optimal Power Flow With Svc Devices By Using The Artificial Bee Colony Algorithm, Kadi̇r Abaci, Volkan Yamaçli, Ali̇ Akdağli

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper a simple and efficient heuristic search method based on the artificial bee colony (ABC) algorithm is presented and used for the optimal power flow (OPF) problem in power systems with static VAR compensator (SVC) devices. The total generation cost of a power system with SVC devices (which improve the voltage stability at load buses) is optimally minimized with the use of ABC. The ABC, which is based on the foraging behavior of honey bees searching for the best food source, is a recently proposed optimization algorithm. The performance of the presented ABC algorithm was tested and verified …

Energy-Efficient And Environmentally Friendly Power Dispatch By Trigeneration With Renewable Energy And Energy Storage, Faisal Pazheri, Mohd Fauzi Othman, Nazar H. Malik, Abdulrehman Ali Al-Arainy

Turkish Journal of Electrical Engineering and Computer Sciences

The importance of energy-efficient power generation that effectively utilizes the available fossil fuels is increasing due to the gradual decline in fossil fuel reserves. Furthermore, concern about global warming has led to rapid growth in renewable energy and energy storage technologies. This trend is encouraging power utilities to effectively exploit the use of renewable energy resources (RESs) and energy storage facilities (ESFs) for power supply systems. In this regards, trigeneration in the presence of RESs and ESFs can play an important role for efficient and clean power dispatch. This paper discusses the optimum power dispatch using a hybrid power plant …

A Problem Approximation Surrogate Model (Pasm) For Fitness Approximation In Optimizing The Quantization Table For The Jpeg Baseline Algorithm, Vinoth Kumar Balasubramanian, Karpagam Manavalan

Turkish Journal of Electrical Engineering and Computer Sciences

The quantization table in the baseline Joint Photographic Experts Group (JPEG) algorithm plays an important role in compression/quality trade-off. Hence the detection of the optimal quantization table is viewed as an optimization problem. The genetic algorithm (GA) is an attractive optimization tool by many researchers for this application due to its ability in dealing with complex problems. In spite of its advantages, the GA requires more computation time to achieve an optimal solution if it has an expensive fitness evaluation. This paper proposes a problem approximation surrogate model (PASM) for fitness approximation to assist the GA in optimizing the quantization …

Optimization Of Pid Parameters Using Bbbc For A Multiarea Agc Scheme In A Deregulated Power System, Nagendra Kumar, Vishal Kumar, Barjeev Tyagi

Turkish Journal of Electrical Engineering and Computer Sciences

Automatic generation control (AGC) is an important service used for the secure and reliable operation of a power system. In this paper, a suitable AGC scheme for a deregulated environment has been studied for various load perturbation scenarios. A proportional integral derivative (PID) controller has been utilized to control the real power output of the generators. The optimal parameters of the PID controller have been determined using the big bang big crunch (BBBC) algorithm, (BBBC-PID). The performance of the BBBC-PID controller has been checked on three different sized multiarea power systems. The results obtained with the applied algorithm have also …

Optimization Design Of A Doubly Salient 8/6 Srm Based On Three Computational Intelligence Methods, Fares Rebahi, Amar Bentounsi, Houssem Rafik El-Hana Bouchekara, Redjem Rebbah

Turkish Journal of Electrical Engineering and Computer Sciences

The aim of this paper is to optimize an 8/6 doubly salient switched reluctance machine using three computational intelligence methods, which include particle swarm optimization, a genetic algorithm, and differential evolution. Three cases are investigated where different parameters are considered like the stator pole arc, rotor pole arc, and ratios, which define the stator yoke and rotor thickness. The objective functions considered are the average torque and the torque-to-weight functions. The simulations are carried out using MATLAB and FEMM software. The optimal results found are compared with the initial design, and it is shown that high improvements are achieved.

A Gis-Based Novel Active Monitoring System For Fiber Networks, Özer Koray Akdemi̇r, Taner Dursun, Sadik Arslan, Recep Benzer, Muhammet Ali̇ Akcayol

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a geographic information system (GIS)-based novel fiber network monitoring system has been developed to improve the operation and maintenance of fiber optic networks (FONs). The main aim of the developed system is to provide the required capabilities for both detailed digital modeling and central monitoring of FONs. The system can perform scheduled measurements and dispatch alarms if any fault or degradation is detected in the concerned FON. It also indicates the alarm locations on a map as a considerable contribution to decreasing mean time to repair. The developed monitoring system has more security features than others.

Optimization With Genetic Algorithm Of Temperature-Dependent Fiber Length Of L-Band Edfa Gain, Murat Yücel, Damt Adnan Mustafa Mustafa

Turkish Journal of Electrical Engineering and Computer Sciences

Erbium-doped fiber amplifiers (EDFAs) have great importance in long-distance communication. It is required to have equal gain for all signals that are transferred and to avoid loss in the receiver of long-distance communication systems. However, temperature dependence changes the output spectrum of the designed gain-flattening systems. In this study, each erbium-doped fiber (EDF) length of a two-stage L-band EDFA has been optimized using a genetic algorithm method; because of the temperature dependence of EDFAs, there is no general rule. Thus, a simple, fast, dynamic, and highly accurate model has been developed and obtained for different EDF lengths that will fix …

A New Deployment Method For Electric Vehicle Charging Infrastructure, Bünyami̇n Yağciteki̇n, Mehmet Uzunoğlu, Ari̇f Karakaş

Turkish Journal of Electrical Engineering and Computer Sciences

The fast depletion of fossil fuels, climate change, and global warming have become major worldwide problems and alternatives for conventional transportation have been actively researched in the last decade. Compared to available conventional vehicles, electric vehicles have a leading position due to their environmentally friendly transportation. Recent electric vehicle penetration brings the necessity of a high number of charging stations, which are considered to be established in community areas such as shopping centers, hospitals, commercial areas, university campuses, residential areas, and streets. Deployment planning of charging stations is very important for driver expectations and social and economic impacts of electric …

Modeling And Performance Optimization Of Photovoltaic And Thermal Collector Hybrid System, Di̇lşad Engi̇n, Meti̇n Çolak

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, the hybrid photovoltaic/thermal collector (PV/T) system's electrical and thermal efficiency was examined by stating a mathematical model and developing a prototype of the system. To enhance the electrical efficiency, the cell temperature of the PV module was decreased with cooling and the heated fluid could be used for low heating applications. For this purpose, a PV/T system was modeled and constructed using a thermal collector placed beneath the photovoltaic panel where the excess heat and solar radiation through the transparent PV module was the input of the thermal collector. A transparent solar module was used in order …