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Multi-objective Parameter Optimization of Four-Stroke Diesel Engine with Waste Cooking Oil Biodiesel and Diesel Blend using RSM-NSGA-ii

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NATIONAL ACADEMY SCIENCE LETTERS-INDIA 2024年第5期47卷 515-520页

作者： Kumar, Pardeep Dhingra, Ashwani Kumar Chhabra, Deepak Chhikara, Ashish Maharshi Dayanand Univ Univ Inst Engn & Technol Dept Mech Engn Rohtak 124001 Haryana India

In the last few decades, there has been sharp increase in consumption of energy around the globe. Due to finite sources of fossil fuels and rise in exhaust emissions resulting into global warming, the researchers have shifted to the petroleum fuel alternatives. The present work considers the different engine input factors (i.e., blending ratio and load) while evaluating the different performance parameters (brake thermal efficiency), combustion (brake-specific fuel consumption), and emission parameters (nitrogen oxide, carbon monoxide, and hydrocarbon) while using waste cooking oil biodiesel in a four-stroke single-cylinder diesel engine. A hybrid RSM coupled with NSGA-ii technique has been considered for optimizing the performance, combustion, and emission characteristics. The novelty of this work is the application of NSGA ii, which has been successfully applied in the simultaneous optimization of brake-specific fuel consumption, brake thermal efficiency, and different emission parameters, viz. carbon monoxide, nitrogen oxide, and hydrocarbon. Five optimum combinations have been evaluated from the 39 Pareto solutions set, and their confirmation tests have also been conducted. From the analysis, the brake thermal efficiency of 31.29% and brake-specific fuel consumption of 0.261 kg/kW-hr along with values of the emissions such as nitrogen oxide: 63.470 ppm, carbon monoxide: 0.085% and hydrocarbons: 20.724 ppm have been achieved. The results are very much within the acceptable limits which confirms the feasibility for the use of waste cooking oil biodiesel in the four-stroke diesel engine.

关键词： Four-stroke single-cylinder diesel engine Multi-objective optimization Response surface methodology nondominated sorting genetic algorithm-ii Central composite design Waste cooking oil biodiesel

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Lifetime maximisation of disjoint wireless sensor networks using multiobjective genetic algorithm

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IET WIRELESS SENSOR SYSTEMS 2018年第5期8卷 200-207页

作者： El-Sherif, Mohamed Fahmy, Yasmine Kamal, Hanan Cairo Univ Fac Engn Elect & Commun Dept Giza Egypt

One of the lifetime maximisation methods for wireless sensor network (WSN) depends on organising the dense sensors into groups which can work in a cooperative sequential manner. Each group contains a subset of sensors that cover all the monitored area and is called a complete cover or simply a cover. Increasing the number of organised covers and maximising the covers lifetime enable longer network lifetime. Here, the authors investigate the WSN lifetime problem as a two-objective optimisation problem. The first objective is to find the maximum number of covers. The second objective considers the problem of wasted energy. Minimising the wasted energy in the critical sensors is achieved by defining a difference factor (DF). The DF is an indication of the difference between the critical sensor lifetime and the cover lifetime. This second objective is compared with other choices in the literature such as minimising the overlapping and minimising the variance. This optimisation problem is addressed using non-dominated sorting genetic algorithm-ii (NSGA-ii). Simulation results are conducted for the network lifetime when using one-objective and different two-objective optimisation problem. The choice of DF as the second objective is proved to overcome drawbacks of other second objectives choices.

关键词： wireless sensor networks genetic algorithms telecommunication network reliability energy measurement minimisation DF two-objective optimisation problem multiobjective genetic algorithm lifetime maximisation methods wireless sensor network WSN lifetime problem nondominated sorting genetic algorithm-ii difference factor NSGA-ii

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Multiobjective Evolutionary algorithm with Risk Minimization Applied to a Fleet Mix Problem

Multiobjective Evolutionary Algorithm with Risk Minimization...

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2010 IEEE World Congress on Computational Intelligence

作者： Willick, Kyle Wesolkowski, Slawomir Mazurek, Michael Canadian Forces Aerosp Warfare Ctr OR Team Ottawa ON Canada DRDC CORA Ottawa ON Canada

ISBN: (纸本)9781424481262

We apply the non-dominated sorting genetic algorithm-ii (NSGA-ii) to a multi-objective fleet-mix problem for risk mitigation. The Stochastic Fleet Estimation (SaFE) model, a Monte Carlo-based model, is used to determine average annual requirements which a fleet must meet. We search for Pareto-optimal combinations of platform-to-task assignments that can be used to complete SaFE generated scenarios. Solutions are evaluated using three objectives, with a goal of minimizing fleet cost, total task duration, and the risk that a solution will not be able to accomplish future scenarios. Optimization over all three objectives allowed for exploration of configurations which were low cost and low risk, a region not explored by prior experiments without the risk objective.

关键词： Monte Carlo based model Monte Carlo methods Pareto optimal combination Pareto optimisation evolutionary computation fleet mix problem genetic algorithms multiobjective evolutionary algorithm nondominated sorting genetic algorithm-ii platform to task assignment risk analysis risk minimization stochastic fleet estimation stochastic processes transportation

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Multi-Objective Clustering Optimization for Multi-Channel Cooperative Sensing in CRNs

Multi-Objective Clustering Optimization for Multi-Channel Co...

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IEEE Global Communications Conference (GLOBECOM)

作者： Celik, Abdulkadir Kamal, Ahmed E. Iowa State Univ Dept Elect & Comp Engn Ames IA 50011 USA

ISBN: (纸本)9781479935123

Cooperative spectrum sensing (CSS) has been extensively studied in the literature to mitigate the weakness of spectrum sensing against hostile propagation phenomenon. Especially for large networks, clustered CSS is preferred to alleviate the energy efficiency, delay and overhead problems. In this study, reporting and sensing channels are first modeled with the consideration of path loss and fading. Then, CSS is divided into three phases: 1) In sensing phase, optimal sensing time is obtained for each local user subject to local detection and false alarm probability thresholds, 2) In reporting phase, adopting Dijkstra's algorithm, multi-hop paths with the maximum success rate and cluster head (CH) selection which gives the mimimum total error rate within each cluster is computed, and 3) In decision phase, collecting independent but unidentically distributed (i.u.d.) member decisions, the CH decides on channel occupancy based on an optimal voting rule for i.u.d. reports. Next, following the phases above, a multi-objective clustering optimization (MOCO) is formulated to select SUs into cluster seeking energy and throughput efficiency goals subject to global detection and false alarm probability constraints. Finally, the Non-dominated sorting genetic algorithm-ii (NSGA-ii) is employed to solve MOCO. Results based on our approach are presented and the merits of this approach are demonstrated.

关键词： cognitive radio cooperative communication genetic algorithms probability radio spectrum management CRN CSS Dijkstra algorithm MOCO NSGA-ii channel occupancy cluster head selection cluster seeking energy cooperative spectrum sensing decision phase false alarm probability thresholds local detection local user maximum success rate multichannel cooperative sensing multiobjective clustering optimization nondominated sorting genetic algorithm-ii optimal sensing time optimal voting rule reporting phase sensing phase throughput efficiency Cascading style sheets Clustering algorithms Fading Sensors Signal to noise ratio Throughput Wireless communication

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Many-objective Extractive Document Text Summarization using NSGA-ii 15

Many-objective Extractive Document Text Summarization using ...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Chhabra, Aayush Singh, Yuvraj Dharmadhikari, Pranav Mitul, Shah Moxesh Soni, Vatsal Nanda, Satyasai Jagannath Malviya National Institute of Technology Department of Electronics and Communication Engineering Jaipur India

ISBN: (纸本)9798350370249

Extractive document text summarization plays an important role in obtaining relevant information from a large article. It finds application in social media analysis, news, legal documents and email summerization. In this manuscript this task is formulated as a many-objective optimization problem by simultaneously minimizing four objective functions: reciprocal of coverage of summery, redundancy of information, reciprocal of proper noun count score and reciprocal of numerical value count score. Along with these four objectives a fixed length of the summery is taken as a constraint. Popular Multi-objective nondominated sorting genetic algorithm-ii (NSGA-ii) is employed to perform the optimization task. The simulation is carried out on two case studies CNN-Daily mail data set. Comprative analysis has been carried out using text summarization with K Means, Fuzzy logic and Fuzzy C-Means method. Performance evaluation using precision shows better results with proposed NSGA-ii, whereas using F-measure the results are second best among the four algorithms. © 2024 IEEE.

关键词： CNN-Daily mail dataset nondominated sorting genetic algorithm-ii Text summarization

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Prediction and optimization in mask-assisted laser transmission microjoining thermoplastic urethane and polyamide 6 through finite-element analysis, Kriging model, and genetic algorithm integrated method

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OPTICAL ENGINEERING 2019年第5期58卷 056106-056106页

作者： Zhou, Jianzhong Zhao, Xuan Li, Jing Meng, Xiankai Jiangsu Univ Sch Mech Engn Zhenjiang Jiangsu Peoples R China

An integrated approach by combining finite-element analysis (FEA), Kriging model, and nondominated sorting genetic algorithm-ii (NSGA-ii) is utilized to realize modeling and optimization in mask-assisted laser transmission microjoining thermoplastic urethane and polyamide 6 (PA6). First, a three-dimensional FEA model is developed for obtaining the simulation data of the temperature field distribution that can determine the molten pool geometry. Then based on the initial training points generated by the optimal Latin hypercube sampling, the relationships between input parameters (laser power P, scanning speed V, and clamping force F) and weld quality [weld width (WW) and shear strength (SS)] are approximated through the Kriging model. Meanwhile, the main effects and contribution rates of various input parameters on the joint performance are discussed. Finally, the optimal weld quality is characterized as maximum SS and WW with a desired value, the NSGA-ii is carried out to solve the multiobjective optimization problem for searching the Pareto-optimal front. The results of validation experiments under the optimal parameters indicate that the corresponding welding joint quality is significantly superior to that under other parameters. (C) 2019 Society of Photo-Optical Instrumentation Engineers (SPIE).

关键词： laser transmission microjoining finite-element analysis Kriging model nondominated sorting genetic algorithm-ii process parameter optimization

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A conflict resolution model for reservoir operation in dry seasons under channel alteration

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JOURNAL OF HYDROLOGY 2022年 610卷

作者： Li, Yu Fu, Xiang Chu, Xuefeng Liu, Shuangjun Wuhan Univ State Key Lab Water Resources & Hydropower Engn S Wuhan Peoples R China Univ Wisconsin Dept Biol Syst Engn Madison WI 53706 USA North Dakota State Univ Dept Civil Construct & Environm Engn Fargo ND USA

The increases in extreme drought events and channel alteration challenge the existing reservoir operation rules. Therefore, reservoir operation should be reconsidered to accommodate these challenges. A conflict resolution model for reservoir operation considering the decision-makers' preference is developed for the conflict between hydropower generation and navigation in dry seasons under channel alteration, to achieve the goal of meeting minimum environmental flow, landslide stability, and river-lake connection constraints. This model with a nondominated sorting genetic algorithm-ii (NSGA-ii) is applied to the Three Gorges Reservoir (TGR) on the Yangtze River. The results show that minimum navigation discharge for the post-dam period is greater than that for the pre-dam period, indicating channel alteration. Both average hydropower generation benefit and navigation reliability decrease with modification of the post-dam minimum navigation discharge, signifying the adverse effect of damming. The total benefits of navigation and hydropower generation decrease with the exceedance probability. A higher hydropower generation benefit leads to a smaller navigation benefit, reflecting the conflict of interest. This study demonstrates the feasibility of the proposed conflict resolution model, as well as the navigation benefit-quantifying method and applicability to similar water resources management problems.

关键词： Reservoir operation Conflict resolution model Drought stress Channel alteration nondominated sorting genetic algorithm-ii Decision-maker preferences

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A hybrid feedforward/feedback multi-channel active control system with optimization for cancelling road noise inside a vehicle cabin

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APPLIED ACOUSTICS 2022年 201卷

作者： Zhang, Shuai Zhang, Lijun Meng, Dejian Zhang, Xiyu Tongji Univ Sch Automot Studies Shanghai 201804 Peoples R China

A hybrid feedforward/feedback multi-channel system was developed for active road noise control (ARNC) inside a vehicle cabin. First, a centralized feedforward subsystem was present with a multi-channel normalized weighted error FxLMS algorithm, including a simplified reference signal normalization method, a reconstructed filter bank for filtering the reference signals, and a newly defined cost function of Aweighting error signals. Second, a distributed feedback subsystem was presented with multiple feedback single-channel simplified normalized FxLMS algorithms. By combining the two subsystems, a hybrid ARNC system was developed. Furthermore, data related to the ARNC system were collected from the test vehicle. Next, a nondominated sorting genetic algorithm-ii was introduced to optimize the system parameter. Multi-objective optimization models of the feedforward and hybrid ARNC systems were established respectively, and the optimal Pareto solution sets for their parameters were obtained. Real-time experiments show that, when the test vehicle driving at 60 km/h on the small brick pavement, the developed hybrid ARNC system can achieve an overall noise reduction of 5.87 dBA in the time domain, and a peak noise reduction of 7.43 dBA in the frequency-domain. Compared with the feedforward ARNC system, road noise reduction is much improved. It still has a good noise reduction effect at other speeds and on different roads. (c) 2022 Elsevier Ltd. All rights reserved.

关键词： Active road noise control Electric vehicle Multi-channel FxLMS algorithm A-weighting error noise nondominated sorting genetic algorithm-ii Distributed system

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Enhancing heat transfer efficiency in corrugated tube heat exchangers: A comprehensive approach through structural optimization and field synergy analysis

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HELIYON 2024年第9期10卷 e30113页

作者： Yu, Chao Shao, Mingzhen Zhang, Wenbao Huang, Mian Wang, Gaugnyi Chinese Acad Sci Changchun Inst Opt Fine Mech & Phys Changchun 130033 Peoples R China

In this paper, a precise and efficient method to optimize corrugated tube heat exchangers is proposed by combining computational fluid dynamics simulation with optimization. The optimization of tubular heat exchangers involves contradictory Colburn coefficient j , and the friction coefficient f , so it is a multi-objective optimization problem. The approximate model is obtained by an extreme learning machine, and the structure parameter of the heat exchanger is optimized by the nondominated sorting genetic algorithm-ii. Compared to the results between the original and optimized tube, the optimized structure Colburn coefficient increased by 5.1 % and the friction coefficient decreased by 9.3 %. Finally, the internal flow field is compared qualitatively from temperature, pressure, and velocity. The optimization effect is further emphasized by using the field synergy theory.

关键词： Corrugated tube heat exchanger Extreme learning machine nondominated sorting genetic algorithm-ii CFD

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A Bi-objective Model for Locating and Allocating in a Green Closed-loop Supply Chain by Probabilistic Customers

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INTERNATIONAL JOURNAL OF ENGINEERING 2024年第11期37卷 2405-2420页

作者： Keramatlou, O. Javadian, N. Didehkhani, H. Islamic Azad Univ Dept Engn Aliabad Katoul Branch Aliabad Katoul Iran Mazandaran Univ Sci & Technol Dept Ind Engn Babol Iran

A closed-loop supply chain model was proposed to optimize the assignment and position of production and distribution centers, product warehouses, retailers, retailer centers, collection, repair, probabilistic customers, and disposal centers. The goal is to minimize environmental pollution and CO(2 )emissions by considering CO2 to O2conversion in vehicle gas converters. Two strategies are explored to determine the best retailer locations based on the predicted movement type (Euclidean Square, Euclidean, Chebyshev, and Rectangular) and expected coverage (time and distance). To compare and select the best strategy, a bi-objective nonlinear programming model was introduced. The model simultaneously examines plans 1 and 2 and chooses the superior plan. Given the strategy selected, a heuristic algorithm is employed to determine the best retailer allocation and locations. Given that the problem is NP-hard in nature, it was solved using a meta-heuristic, the non-dominated sorting genetic algorithm. Finally, to validate the effectiveness, a numerical example is presented and solved using optimization software. The algorithm's findings demonstrate a strong correlation with meta-heuristic algorithms, indicating it as a promising starting point that can be further enhanced by incorporating such methods. For instance, the optimized suggestion algorithm resulted in a reduction of 739 units in carbon dioxide emissions, while the genetic algorithm achieved a reduction of 703 units. Furthermore, the cost computed by the algorithm stands at 7,484,935 units, a figure close to the output of 7,030,846 units generated by the genetic algorithms.

关键词： Green Closed-loop Supply Chain Retailers Services Customer Services nondominated sorting genetic algorithm-ii

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