The study of reducing the cost of investment in wind energy based on the cat swarm optimization with high reliability

The vehicle’s maintenance costs, uptime and security are the most important goals for owners and transport companies, but these goals are conflictual and the major cause for delays is related to the maintenance policies. The main objective of transporters is to respond properly to their customer’s demands. In order to deal with this competitiveness, transport companies are working to improve the management of their fleets by focusing in particular on vehicle maintenance, which impact the vehicles uptime, and generate the most important cost. In addition, a vehicle maintenance policy aims to avoid failures and keep the vehicle up and safe. This objective is reached by ensuring a high reliability; otherwise, an unexpected failure of a component can cause vehicle down and can affect the entire sub-system while generating costs. In this paper, we propose a new maintenance policy based on multi-objective optimization. This problem is solved using the Speed-Constrained Multiobjective Particle Swarm Optimization (SMPSO) for an instance of 18 components and 20 vehicles. First, we give an overview of the existing techniques used for vehicle’s maintenance policy, then we present the mathematical model that describes the cost of maintenance and the level of safety. Numerical experiments are presented to demonstrate the efficiency of our approach.

Download Full-text

Optimizing channel cross-section based on cat swarm optimization

Water Science & Technology Water Supply ◽

10.2166/ws.2015.128 ◽

2015 ◽

Vol 16 (1) ◽

pp. 219-228 ◽

Cited By ~ 3

Author(s):

Dong Liu ◽

Yuxiang Hu ◽

Qiang Fu ◽

Khan M. Imran

Keyword(s):

Cross Section ◽

Optimization Technique ◽

Land Acquisition ◽

Open Channels ◽

Channel Cross Section ◽

Concrete Lining ◽

Swarm Optimization ◽

Channel Section ◽

Cat Swarm Optimization ◽

The Cost

Optimal design of channel cross-section is an important task in the hydraulic design of open channels. The traditional methods and models which neglect the frost heave are trial procedures and may result in failure of channels in design of irrigation channels. To improve the total cost, reliability and effectiveness, the model which is used in this study, is not only minimizing the cost of land acquisition but also the cost of concrete lining considering cost as the objective function. The constrained optimization model which considers values of thickness of channel concrete slab constraint simultaneously along with the objective of minimization of cost is propounded and solved using a recent global optimization technique, namely cat swarm optimization (CSO). The optimized channel section not only satisfies the optimal hydraulic cross-section but guarantees the safety and stability of the side walls so that both the amount of the concrete lining and the land acquisition are optimized. Finally, we take a main channel of Qinghe Irrigated Area of Farm 853 in Heilongjiang Province as a study area. The results obtained using the CSO approach are satisfaction and the method can be used for reliable design of artificial open channels. Furthermore, we compare the CSO algorithm with a genetic algorithm (GA) and the particle swarm optimization (PSO) to verify the effectiveness of the cat swarm algorithm in the channel section optimization.

Download Full-text

Fuzzy multi-objective location and routing problem

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-191654 ◽

2020 ◽

Vol 39 (3) ◽

pp. 3259-3273

Author(s):

Nasser Shahsavari-Pour ◽

Najmeh Bahram-Pour ◽

Mojde Kazemi

Keyword(s):

Firefly Algorithm ◽

High Reliability ◽

Research Area ◽

Nsga Ii ◽

Location Routing Problem ◽

Routing Problem ◽

Location Allocation ◽

Multi Objective ◽

Location Routing ◽

The Cost

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.

Download Full-text

Case Study—Failure Analysis of a Multiplexer

ISTFA 2016: Conference Proceedings from the 42nd International Symposium for Testing and Failure Analysis ◽

10.31399/asm.cp.istfa2016p0243 ◽

2016 ◽

Author(s):

Michael Woo ◽

Marcos Campos ◽

Luigi Aranda

Keyword(s):

Failure Analysis ◽

High Reliability ◽

Component Failure ◽

Root Cause ◽

Knowing That ◽

Cause Of Failure ◽

The Cost

Abstract A component failure has the potential to significantly impact the cost, manufacturing schedule, and/or the perceived reliability of a system, especially if the root cause of the failure is not known. A failure analysis is often key to mitigating the effects of a componentlevel failure to a customer or a system; minimizing schedule slips, minimizing related accrued costs to the customer, and allowing for the completion of the system with confidence that the reliability of the product had not been compromised. This case study will show how a detailed and systemic failure analysis was able to determine the exact cause of failure of a multiplexer in a high-reliability system, which allowed the manufacturer to confidently proceed with production knowing that the failure was not a systemic issue, but rather that it was a random “one time” event.

Download Full-text

Harnessing Wind Energy Potential in ASEAN: Modelling and Policy Implications

Sustainability ◽

10.3390/su13084279 ◽

2021 ◽

Vol 13 (8) ◽

pp. 4279

Author(s):

Youngho Chang ◽

Phoumin Han

Keyword(s):

Wind Energy ◽

Carbon Emissions ◽

Policy Implications ◽

Wind Generation ◽

Energy Potential ◽

Trade Model ◽

Electricity Trade ◽

Generation Capacity ◽

The Cost ◽

Business As Usual

This study examines whether and how harnessing more wind energy can decrease the cost of meeting the demand for electricity and amount of carbon emissions in the Association for Southeast Asian Nations (ASEAN) region, using the ASEAN integrated electricity trade model. Three scenarios are considered: a counterfactual business-as-usual (BAU) scenario, which assumes no wind energy is used; an actual BAU scenario that uses the wind-generation capacity in 2018; and a REmap scenario, which employs the wind-generation capacity from the Renewable Energy Outlook for ASEAN. Simulation results suggest that dispatching more wind energy decreases the cost of meeting the demand for electricity and amount of carbon emissions. However, these emissions increase during the late years of the study period, as the no- or low-emitting energy-generation technologies are crowded out.

Download Full-text

Deep autoencoder-based community detection in complex networks with particle swarm optimization and continuation algorithms

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-201342 ◽

2021 ◽

pp. 1-17

Author(s):

Mohammed Al-Andoli ◽

Wooi Ping Cheah ◽

Shing Chiang Tan

Keyword(s):

Particle Swarm Optimization ◽

Complex Networks ◽

Learning Community ◽

Community Detection ◽

Particle Swarm ◽

Premature Convergence ◽

Swarm Optimization ◽

Detection Algorithms ◽

Real World Datasets ◽

The Cost

Detecting communities is an important multidisciplinary research discipline and is considered vital to understand the structure of complex networks. Deep autoencoders have been successfully proposed to solve the problem of community detection. However, existing models in the literature are trained based on gradient descent optimization with the backpropagation algorithm, which is known to converge to local minima and prove inefficient, especially in big data scenarios. To tackle these drawbacks, this work proposed a novel deep autoencoder with Particle Swarm Optimization (PSO) and continuation algorithms to reveal community structures in complex networks. The PSO and continuation algorithms were utilized to avoid the local minimum and premature convergence, and to reduce overall training execution time. Two objective functions were also employed in the proposed model: minimizing the cost function of the autoencoder, and maximizing the modularity function, which refers to the quality of the detected communities. This work also proposed other methods to work in the absence of continuation, and to enable premature convergence. Extensive empirical experiments on 11 publically-available real-world datasets demonstrated that the proposed method is effective and promising for deriving communities in complex networks, as well as outperforming state-of-the-art deep learning community detection algorithms.

Download Full-text

Comparison of SVC and TCSC Installation in Transmission Line with Loss Minimization and Cost of Installation via Particle Swarm Optimization

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.785.495 ◽

2015 ◽

Vol 785 ◽

pp. 495-499

Author(s):

Siti Amely Jumaat ◽

Ismail Musirin

Keyword(s):

Particle Swarm Optimization ◽

Transmission Line ◽

Objective Function ◽

Transmission Loss ◽

Particle Swarm ◽

Static Var Compensator ◽

Loss Minimization ◽

Swarm Optimization ◽

The Cost ◽

Thyristor Controlled Series Compensator

The paper presents a comparison of performance Static Var Compensator (SVC) and Thyristor Controlled Series Compensator (TCSC) with objective function to minimize the transmission loss, improve the voltage and monitoring the cost of installation. Simulation performed on standard IEEE 30-Bus RTS and indicated that EPSO a feasible to achieve the objective function.

Download Full-text