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evolutionary algorithm for Software Project Scheduling Considering Team Relationships

IEEE ACCESS 2023年 11卷 43690-43706页

作者： Zhang, Jianhao Shen, Xiaoning Yao, Chengbin Nanjing Univ Informat Sci & Technol Sch Automat Nanjing 210044 Jiangsu Peoples R China Jiangsu Key Lab Big Data Anal Technol Nanjing 210044 Jiangsu Peoples R China Jiangsu Engn Res Ctr Meteorol Energy Using & Contr Nanjing 210044 Jiangsu Peoples R China Jiangsu Collaborat Innovat Ctr Atmospher Environm Nanjing 210044 Jiangsu Peoples R China

Human relationships have a great impact on the software development process. Meanwhile, project development may require the acquisition of new skills that employees have not yet acquired due to changes in customer requirements. However, such factors are seldom incorporated into software project scheduling problem. To address this, a novel mathematical model considering the team relationships is established for software project scheduling problem. This model introduces the communication cost factor of each employee, and analyses its quantitative connections with changes in human relationships and the growth of skill proficiency respectively. In addition, a selection mechanism for external employees is designed to meet new skill requirements. To solve the model, an improved bi-population discrete evolutionary algorithm based on information feedback is proposed. The heuristic information of "employee suitability" is utilized in initialization to obtain better initial individuals. The feedback mechanism based on "evolutionary quality" is applied to provide an effective strategy for adaptive tuning of subpopulation size. The selection probabilities of distinct crossover operators are adjusted according to the "improved quantity" to increase crossover efficiency. Moreover, an enhanced local search strategy based on the "degree of team cooperation" and the "improved quantity" is developed. Experimental results show that by considering human relationships under different communication cost factors, the duration and cost of the project are significantly reduced. Compared with four state-of-the-art algorithms, the scheduling performance of the proposed algorithm can be improved by 10.6374% to 25.8566%.

关键词： Software Task analysis Costs Software algorithms evolutionary computation Optimization Optimal scheduling Software project scheduling communication cost human relationship information feedback evolutionary algorithm

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evolutionary algorithm for advanced process planning and scheduling in a multi-plant

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COMPUTERS & INDUSTRIAL ENGINEERING 2005年第2期48卷 311-325页

作者： Moon, C Seo, Y Korea Univ Dept Ind & Informat Engn Seoul 136701 South Korea Hanyang Univ Dept Informat & Ind Engn Ansan 425791 South Korea

Integration of process planning and scheduling is one of the most important functions to support flexible planning in a multi-plant. The planning and scheduling are actually interrelated and should be solved simultaneously. In this paper, we propose an advanced process planning and scheduling model for the multi-plant. The objective of the model is to decide the schedules for minimizing makespan and operation sequences with machine selections considering precedence constraints, flexible sequences, and alternative machines. The problem is formulated as a mathematical model, and an evolutionary algorithm is developed to solve the model. Numerous experiments arc carried out to demonstrate the efficiency of the proposed approach. (c) 2005 Elsevier Ltd. All rights reserved.

关键词： process planning and scheduling multi-plant chain TSP with precedence constraint evolutionary algorithm

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evolutionary algorithm based structure search and first-principles study of B₁₂C₃ polytypes

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JOURNAL OF ALLOYS AND COMPOUNDS 2017年 695卷 2023-2034页

作者： Pillai, Harikrishnan Gopalakrishna Madam, Ajith Kulangara Chandra, Sharat Cheruvalath, Valsakumar Mundachali NITK Dept Phys Surathkal 575025 Karnataka India IGCAR Div Mat Phys Kalpakkam 603102 Tamil Nadu India Indian Inst Technol IIT Palakkad Dept Phys Palakkad 678557 Kerala India

The structure search based on evolutionary algorithm has yielded six unique Boron Carbide structures in B12C3 stoichiometry, three of them with negative formation energies. Their formation energies lie within a band of 166 meV/atom, so they can be formed together in any optimal high temperature synthesis of B12C3 and they are thermodynamically stable at temperatures up to 660 K. This work is the first independent confirmation using structure search that B11Cp(CBC) is the ground state structure of B12C3 stoichiometry. New structures like the 14-atom-cage and the supercell (B11Cp)(B10C2pe)(CBC)(CBB) have also emerged in the structure search. Five structures have base-centered monoclinic symmetry and the supercell has triclinic symmetry, implying that the determination of monoclinic symmetry in B12C3 by experimental measurements is an option for further inquiry. The mechanical stability of these systems are established through the analysis of their elastic constants and their dynamical stability from the phonon data. The high value of Bulk modulus (similar to 250 GPa) indicates their high hardness and the B/G value confirms their brittle nature. The electronic structure shows that they are semiconductors with a significant reduction in the band gap when the structure does not contain the CBC chain. The curve fitting of the cumulative IR spectrum against the experimental spectrum implies that the presence of B11Cp(CBC) in the ground state composition could mostly be through structures of larger unit cells. The hardness values of these systems estimated by using the semi-empirical model based on bond strength are in excellent agreement with the experimental values. For the four structures with chain the hardness values are close to the superhard regime (>40 GPa). (C) 2016 Elsevier B.V. All rights reserved.

关键词： Boron Carbides Density functional theory evolutionary algorithm Hardness

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evolutionary algorithm based classifier parameter tuning for automatic diabetic retinopathy grading: A hybrid feature extraction approach

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KNOWLEDGE-BASED SYSTEMS 2013年第Feb.期39卷 9-22页

作者： Mookiah, M. R. K. Acharya, U. Rajendra Martis, Roshan Joy Chua, Chua Kuang Lim, C. M. Ng, E. Y. K. Laude, Augustinus Ngee Ann Polytech Dept Elect & Comp Engn Singapore 599489 Singapore Univ Malaya Fac Engn Dept Biomed Engn Kuala Lumpur Malaysia Nanyang Technol Univ Sch Mech & Aerosp Engn Singapore 639798 Singapore Tan Tack Seng Hosp Inst Eye Natl Healthcare Grp Singapore Singapore

Human eye is one of the most sophisticated organ, with retina, pupil, iris cornea, lens and optic nerve. Automatic retinal image analysis is emerging as an important screening tool for early detection of eye diseases. Uncontrolled diabetes retinopathy (DR) and glaucoma may lead to blindness. DR is caused by damage to the small blood vessels of the retina in the posterior part of the eye of the diabetic patient. The main stages of DR are non-proliferate diabetes retinopathy (NPDR) and proliferate diabetes retinopathy (PDR). The retinal fundus photographs are widely used in the diagnosis and treatment of various eye diseases in clinics. It is also one of the main resources used for mass screening of DR. We present an automatic screening system for the detection of normal and DR stages (NPDR and PDR). The proposed systems involves processing of fundus images for extraction of abnormal signs, such as area of hard exudates, area of blood vessels, bifurcation points, texture and entropies. Our protocol uses total of 156 subjects consisting of two stages of DR and normal. In this work, we have fed thirteen statistically significant (p < 0.0001) features for Probabilistic Neural Network (PNN), Decision Tree (DT) C4.5, and Support Vector Machine (SVM) to select the best classifier. The best model parameter (sigma) for which the PNN classifier performed best was identified using global optimization techniques such as Genetic algorithm (GA) and Particle Swarm Optimization (PSO). We demonstrated an average classification accuracy of 96.15%, sensitivity of 96.27% and specificity of 96.08% for sigma = 0.0104 using threefold cross validation using PNN classifier. The computer-aided diagnosis (CAD) results were validated by comparing with expert ophthalmologists. The proposed automated system can aid clinicians to make a faster DR diagnosis during the mass screening of normal/DR images. (c) 2012 Elsevier B.V. All rights reserved.

关键词： Diabetic retinopathy Bifurcation point Local binary pattern Laws texture energy evolutionary algorithm

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evolutionary algorithm-based fuzzy PD control of spillway gates of dams

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JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 2007年第8期344卷 1039-1055页

作者： Bagis, Aytekin Karaboga, Dervis Erciyes Univ Dept Elect Elect Engn TR-38039 Kayseri Turkey Erciyes Univ Dept Comp Engn TR-38039 Kayseri Turkey

In this paper, an evolutionary algorithm ( EA)-based fuzzy proportional-derivative (PD)-type controller is employed to reservoir control of dams with the purpose of operating spillway gates during any flood of any magnitude, which is not predictable beforehand. EA is used to evolve the main parameters of the fuzzy PD controller. The use of the EA, in conjunction with a systematic neighborhood structure for the determining of fuzzy rule-base parameters, leads to a significant improvement in the performance of the controller. The major objective of the controller is to achieve better system performance over the conventional control methods. In order to demonstrate the high performance of the presented method, we simulate the control system using different probable inflow hydrographs of various magnitudes. The simulation results indicate that the EA-based fuzzy PD controller not only performs an accurate and efficient solution, but also exhibits more desirable and reliable results than the conventional approaches. (c) 2007 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

关键词： fuzzy PD control evolutionary algorithm spillway gate reservoir operation

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evolutionary algorithm-Based Adaptive Robust Optimization for AC Security Constrained Unit Commitment Considering Renewable Energy Sources and Shunt FACTS Devices

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IEEE ACCESS 2021年 9卷 123575-123587页

作者： Baziar, Aliasghar Bo, Rui Ghotbabadi, Misagh Dehghani Veisi, Mehdi Ur Rehman, Waqas Missouri Univ Sci & Technol Dept Elect & Comp Engn Rolla MO 65409 USA Mapna Operat & Maintenance Co Dept Elect Engn Tehran *** Iran Islamic Azad Univ Sama Tech & Vocat Training Coll Tehran Branch Teh Tehran *** Iran

An AC security constrained unit commitment (AC-SCUC) in the presence of the renewable energy sources (RESs) and shunt flexible AC transmission system (FACTS) devices is conventionally modeled as a deterministic optimization problem to minimize the operation cost of conventional generation units (CGUs) subject to AC optimal power flow (AC-OPF) equations, operation constraints of RESs, shunt FACTS devices, and CGUs. To cope with the uncertainties of load and RES generation, robust and stochastic optimization and linearized formulation have been used to achieve a sub-optimal solution. To arrive at a more optimal solution, an evolutionary algorithm-based adaptive robust optimization (EA-ARO) approach to solve the non-linear and non-convex optimization problem was proposed. A hybrid solver of grey wolf optimization (GWO) and teaching learning-based optimization (TLBO) was proposed to solve the AC-SCUC problem in the worst-case scenario to obtain robust and reliable optimal solution. Finally, the proposed method was simulated on standard IEEE test systems to demonstrate its capabilities, and the results showed the proposed hybrid solver obtained robust optimal solutions with reduced computation time and standard deviation. Moreover, the numerical results proved the proposed strategy's capabilities of improving the economics of generation units, such as lower operational cost, and enhancing the performance of the transmission networks, such as improved voltage profile and reduced energy losses.

关键词： Computational modeling Load modeling Optimization Stochastic processes Uncertainty Security Reactive power AC security constrained unit commitment evolutionary algorithm adaptive robust optimization shunt FACTS devices renewable energy sources

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evolutionary algorithm with ensemble strategies based on maximum a posteriori for continuous optimization

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INFORMATION SCIENCES 2018年 460卷 1-22页

作者： Ghoumari, Asmaa Nakib, Amir Siarry, Patrick France Lab Images Signaux & Syst Intelligents LIS EA 9656 122 Rue Paul Armangot F-94400 Vitry Sur Seine France

To be efficient and reach the best solution, evolutionary algorithms (EAs) are composed of three evolutionary operators: selection, crossover and mutation. Nevertheless, there is no established rule to choose them from a large panel of operators available in the literature. In this paper, a Maximum A Posteriori (MAP) principle based rule is proposed to palliate the operators' selection problem for solving different kinds of continuous optimization problems. This learning based approach allows switching between different strategies during the optimization. This algorithm is called Maximum a posteriori based evolutionary algorithm (MEA). Experimental analysis was performed and proved its efficiency and robustness on a large set of 34 problems. (C) 2018 Elsevier Inc. All rights reserved.

关键词： Continuous optimization Metaheuristic Learning Maximum a posteriori evolutionary algorithm

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evolutionary algorithm for Water Storage Forecasting Response to Climate Change with Small Data Sets: The Wolonghu Wetland, China

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ENVIRONMENTAL ENGINEERING SCIENCE 2012年第8期29卷 814-820页

作者： Ni, Qingwei Wang, Li Zheng, Binghui Sivakumar, M. Wuhan Univ Sci & Technol Coll Resources & Environm Engn Wuhan 430081 Peoples R China Chinese Res Inst Environm Sci State Environm Protect Key Lab Estuary & Coastal Beijing Peoples R China Univ Wollongong Fac Engn Sustainable Earth Res Ctr Wollongong NSW Australia

A novel genetic programming (GP) technique, a new method of evolutionary algorithms, was applied to a small data set to predict the water storage of Wolonghu wetland in response to the climate change in the northeastern part of China. Fourteen years (1993-2006) of annual water storage and climatic data of the wetland were used for model training and testing. Results of simulations and predictions illustrate a good fit between calculated water storage and observed values (mean absolute percent error = 9.47, r = 0.99). By comparison, a multilayer perceptron method (a popular artificial neural network model) and Grey theory model with the same data set were applied for performance estimation. It was found that GP technique had better performance than the other two methods, in both the simulation step and the predicting phase. The case study confirms that GP method is a promising way for wetland managers to make a quick estimation of fluctuations of water storage in some wetlands under the limitation of a small data set.

关键词： water storage small data set evolutionary algorithm Wolonghu wetland

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evolutionary algorithm-based optimisation of the signal-to-noise ratio for indoor visible-light communication utilising white light-emitting diode

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IET OPTOELECTRONICS 2012年第6期6卷 307-317页

作者： Ding, J. P. Ji, Y. F. Beijing Univ Posts & Telecommun State Key Lab Informat Photon & Opt Commun Beijing 100876 Peoples R China

Visible-light communication system that utilises white light-emitting diode (LED) lighting equipment has been proposed and expected to provide uniform wireless communications and illumination simultaneously. Owing to multipath transmission channel characteristics, up to now, it is still challenging to obtain uniform signal-to-noise ratio (SNR) for each position within the indoor environment. In this study, an evolutionary algorithm (EA)-based alternative scheme is proposed to optimise the SNR distribution for indoor visible-light communication systems. Presented analysis shows that in three distributed lighting configurations, when the optical powers of individual white LED lighting equipment are dynamically controlled by tailored EA, the dynamic range of SNR referenced against the peak SNR can be reduced by up to about 24.7% whereas the uniformity illuminance ratio is improved from less than 0.63 to over 0.70 with the impact to root-mean-square delay spread is negligible. Furthermore, the relationship between the field of view of receivers and the optimisation performance is presented as well.

关键词： multipath transmission channel evolutionary algorithm optical links uniform wireless communications white light emitting diode evolutionary computation signal-to-noise ratio white LED lighting equipment Optical communication equipment Free-space optical links Optimisation techniques Light emitting diodes indoor communication light emitting diodes optical communication equipment indoor visible light communication

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evolutionary algorithm applied to time-series landing flight path and control optimization of supersonic transport

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NEURAL COMPUTING & APPLICATIONS 2023年第2期35卷 1211-1223页

作者： Kanazaki, Masahiro Setoguchi, Nao Saisyo, Ryouta Tokyo Metropolitan Univ 6-6 Asahigaoka Hino Tokyo 1920065 Japan

An evolutionary algorithm (EA) was applied in this study to optimize the landing flight path of a delta-winged supersonic transport (SST). However, it is difficult for a delta wing with a large sweepback angle to reduce the aerodynamic drag during supersonic cruising to gain sufficient lift force at low speeds, particularly during takeoff and landing. Besides, high-fidelity computational fluid dynamics is required to evaluate the flight path with a complex flowfield. This study performed an efficient flight simulation based on the Kriging model-assisted aerodynamic estimation to carry out global optimization. Then, the designs of the flight and control sequence were realized for time-series optimization of effective SST landing. To develop the EA, two design scenarios were considered;one involved only the elevator, which is an aerodynamic control surface that controls the aircraft, and the other involved introducing thrust control in addition to elevator control. In the scenario involving only elevator control, feasible solutions could not be obtained owing to the poor low-speed aerodynamic performance of the SST. This paper presents several feasible solutions enabling reasonable SST landing performance in the scenario involving the elevator and thrust controls along with descriptions regarding the optimum flight and control sequences. In addition, we analyzed the solutions by analyzing the variance to obtain qualitative information. Consequently, we determined that elevator control was considerably effective in cases with the microburst effect than in cases without the microburst effect.

关键词： evolutionary algorithm Constrained multi-objective problem Aerodynamic flight simulation Supersonic transport Time-series optimization Real-world application

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