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Robust Periodic Vehicle Routing Problem with Time Windows under Uncertainty: An Efficient algorithm

KSCE JOURNAL OF CIVIL ENGINEERING 2018年第11期22卷 4626-4634页

作者： Salamatbakhsh-Varjovi, A. Tavakkoli-Moghaddam, R. Alinaghian, M. Najafi, E. Islamic Azad Univ Sci & Res Branch Dept Ind Engn Tehran *** Iran Univ Tehran Sch Ind Engn Coll Engn Tehran 141556619 Iran Arts & Metiers Paris Tech LCFC Metz France Isfahan Univ Technol Dept Ind & Syst Engn Esfahan 841583111 Iran

In a competitive environment, distributors engage in intense rivalry to meet the customers' demands and accordingly earn maximum profits. Due to changes in customers' demands, changes in a planned combination of customers to be visited in various days, traffic changes, etc., a sequence of visiting customers by competitors will be changed. So, planning for serving customers ahead of competitors will be uncertain. On the other hand, total transportation costs are also of high importance in distribution of goods. By keeping this issue in mind, we develop a bi-objective mathematical model to evaluate a Periodic Vehicle Routing Problem (PVRP) with time windows under uncertainty for companies competing to provide services to customers. The model is established using an improved scenario-based robust optimization approach. Given that the PVRP is an NP-hard problem, an Improved differential evolution (IDE) algorithm is used to identify efficient solutions for the model. The results on small-scale problems were compared with those obtained using the CPLEX solver. To evaluate the performance of the proposed IDE algorithm, a few sample tests on large-scale problems are conducted, and the results are compared with those derived using two other differential evolution algorithms. The findings show that the IDE algorithm exhibits suitable accuracy and performance in solving the presented model.

关键词： periodic vehicle routing problem robust optimization time window differential evolution algorithm

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Exergy analysis and multiobjective optimization of a biomass gasification based multigeneration system

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2018年第5期43卷 2631-2644页

作者： Rashidi, Halimeh Khorshidi, Jamshid Univ Hormozgan Fac Engn Bandar Abbas Iran

Biomass gasification is a process of converting biomass to a combustible gas suitable for use in boilers, engines and turbines to produce combined cooling, heat and power. This paper presents a detailed model of a biomass gasification system and designs a multi generation energy system which uses the biomass gasification process for generating combined cooling, heat and electricity. Energy and exergy analyses are first applied to evaluate the performance of the designed system. Next, minimizing total cost rate and maximizing exergy efficiency of the system are considered as two objective functions and a multiobjective optimization approach based on differential evolution algorithm and local unimodal sampling technique is developed to calculate the optimal values of the multi generation system parameters. A parametric study is then carried out and Pareto front curve is used to determine the trend of objective functions and assess the performance of the system. Furthermore, a sensitivity analysis is employed to evaluate effects of design parameters on the objective functions. Simulation results are compared with two other multiobjective optimization algorithms and effectiveness of the proposed method is verified using various performance indicators. (C) 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

关键词： Multi-objective optimization Exergy analysis Pareto front Biomass gasification differential evolution algorithm Local unimodal sampling

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Load frequency control problem in interconnected power systems using robust fractional PI^λD controller

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AIN SHAMS ENGINEERING JOURNAL 2018年第1期9卷 77-88页

作者： Delassi, Abdelmoumene Arif, Salem Mokrani, Lakhdar Univ Amar Telidji Laghouat Lab Anal & Commande Syst Energie & Reseaux Elect BP 37G Laghouat 03000 Algeria

In this paper, a robust Fractional Order (PID)-D-lambda controller that contains an integral fraction action and a simple filtered derivative action, is investigated on Automatic Generation Control (AGC) of a three areas reheat-thermal system. For more realistic study some nonlinear constraints have been introduced such as Governor Dead Band (GDB), Generation Rate Constraints (GRC) and boiler dynamics. The optimal controller parameters are tuned through new evolutionary algorithm known as differential evolution (DE) algorithm by minimizing the Integral of Squared Error (ISE) index. Obtained results reveal clearly the superiority of the investigated controller compared to the other controllers such as PID, PID mu and (PID mu)-D-lambda in terms of the performance index, peak overshoots, peak undershoots and settling time. Effectiveness and rapidity of the DE algorithm in the convergence have been shown and compared to Genetic algorithm (GA). Finally, robustness analysis against higher degree of load disturbance and sever parametric variation demonstrates the effectiveness of the investigated controller. (C) 2015 Faculty of Engineering, Ain Shams University. Production and hosting by Elsevier B.V.

关键词： Load frequency control Fractional controller differential evolution algorithm Nonlinearities Integral of Squared Error

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On the Impossibility of Building a Thau Observer for a Nonlinear Model of an Induction Motor

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IEEE LATIN AMERICA TRANSACTIONS 2018年第7期16卷 1870-1877页

作者： Perez, J. H. Santiago, E. Figueroa, M. Pacheco, J. Avila, D. Tamayo, P. A. Mancilla, J. E. Flores, L. A. Inst Politecn Nacl SEPI ESIME Azcapotzalco Mexico City DF Mexico Inst Politecn Nacl CIDETEC Mexico City DF Mexico

Given the simplicity of Thau observer, it could be attractive to try to build this kind of observer for an induction motor. However, in this paper, (metaheuristic) arguments are provided to explain why such purpose cannot be accomplished. In order to establish the impossibility of developing a Thau observer for the nonlinear model of an induction motor, first, it must be verified that Thau inequality cannot be satisfied. Therefore, Lipschitz constant for nonlinear model of the motor was determined. Next, given the absence of a systematic procedure of design and due to the great diversity of possible values for observer parameters, Thau relation should be maximized. Nevertheless, as this last task is difficult and in order to avoid the drawbacks of classical methods, in this work, differential evolution algorithm was used. In spite of having maximized successfully Thau relation, Thau inequality could not be satisfied. As a last attempt, the motor model was scaled. Lipschitz constant for this model was minimized and Thau relation was again maximized Notwithstanding, Thau inequality could not be satisfied for scaled model. Based on exhaustive bibliographic searches, it can be assured that this is the first time that this kind of problem is considered in the technical literature.

关键词： induction motor nonlinear observer Thau inequality Lipschitz constant differential evolution algorithm

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A plus evolutionary search algorithm and QR decomposition based rotation invariant crossover operator

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EXPERT SYSTEMS WITH APPLICATIONS 2018年 103卷 49-62页

作者： Civicioglu, Pinar Besdok, Erkan Erciyes Univ Dept Aircraft Elect & Elect Fac Aeronaut & Astronaut Kayseri Turkey Erciyes Univ Fac Engn Dept Geomat Engn Kayseri Turkey

The recently proposed artificial cooperative search (ACS) algorithm is a population-based iterative evolutionary algorithm (EA) for solving real-valued numerical optimization problems. It uses a rotation-invariant line recombination-based mutation strategy and rule-based crossover operator. However, it performs poorly for problems that include closely-related variables because, in these cases, generating uncorrelated feasible trial solution vectors using stochastic crossover methods is extremely difficult, and its mutation and crossover operators are also less effective. This paper adds a new QR-decomposition-based rotation-invariant search strategy to the ACS algorithm to improve its ability to solve such problems. This new, advanced ACS algorithm, called A+, has only one control parameter, alpha, and experimental results have shown that its performance does not strongly depend on the initial value of alpha. This paper also examines A+'s performance for noisy point cloud filtering, which is a complex real-world problem. The results of numerical experiments demonstrate that A+'s performance when solving numerical and real-world problems with closely-related variables is better than those of the comparison algorithms. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Artificial cooperative search algorithm Artificial bee colony algorithm Backtracking search optimization algorithm Cuckoo search algorithm CMAES differential evolution algorithm

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International asset allocation optimization with fuzzy return

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KNOWLEDGE-BASED SYSTEMS 2018年 139卷 189-199页

作者： Liu, Yong Jun Zhang, Wei-Guo Gupta, Pankaj South China Univ Technol Sch Business Adm Guangzhou 510641 Guangdong Peoples R China Univ Delhi Dept Operat Res Delhi India

This paper investigates an international asset allocation problem in a fuzzy uncertain environment, where the risk attitudes of investors are taken into consideration. Since investors are usually risk aversion, we use the possibilistic risk premium index to measure their required compensation for implementing a venture investment in the paper. Then, we present a possibilistic international asset allocation optimization model with realistic constraints. The main features of the proposed model are that we represent investors' risk preferences by the commonly-used hyperbolic absolute risk aversion (HARA) utility function, and incorporate some realistic constraints into the proposed model to simulate the transaction in the real world financial markets. To solve the proposed model, we design a time variant differential evolution with harmony search (TVDEHS) algorithm in the paper. Finally, we provide a numerical example to demonstrate the application of the proposed model and highlight the performance of the designed algorithm. (C) 2017 Elsevier B.V. All rights reserved.

关键词： International asset allocation Fuzzy set theory HARA utility differential evolution algorithm

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Two-stage update biogeography-based optimization using differential evolution algorithm (DBBO)

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COMPUTERS & OPERATIONS RESEARCH 2011年第8期38卷 1188-1198页

作者： Boussaid, Ilhem Chatterjee, Amitava Siarry, Patrick Ahmed-Nacer, Mohamed Univ Paris Est Creteil Val de Marne LiSSi EA 3956 F-94010 Creteil France Univ Sci & Technol Houari Boumediene Dept Elect Engn & Comp Sci Algiers 16111 Algeria Jadavpur Univ Dept Elect Engn Kolkata 700032 W Bengal India

The present paper proposes a new stochastic optimization algorithm as a hybridization of a relatively recent stochastic optimization algorithm, called biogeography-based optimization (BBO) with the differential evolution (DE) algorithm. This combination incorporates DE algorithm into the optimization procedure of BBO with an attempt to incorporate diversity to overcome stagnation at local optima. We also propose to implement an additional selection procedure for BBO, which preserves fitter habitats for subsequent generations. The proposed variation of BBO, named DBBO, is tested for several benchmark function optimization problems. The results show that DBBO can significantly outperform the basic BBO algorithm and can mostly emerge as the best solution providing algorithm among competing BBO and DE algorithms. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Biogeography-based optimization differential evolution algorithm

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Power Density Analysis and Optimization of SMPMSM Based on FEM, DE algorithm and Response Surface Methodology

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ENERGIES 2019年第19期12卷

作者： Hao, Jinshun Suo, Shuangfu Yang, Yiyong Wang, Yang Wang, Wenjie China Univ Geosci Beijing Sch Engn & Technol Beijing 100083 Peoples R China Tsinghua Univ State Key Lab Tribol Beijing 100084 Peoples R China

Surface-mounted permanent magnet synchronous motors (SMPMSM) with high power density and good speed regulation are widely used in industrial applications. In order to further improve its power density, this paper studied the relationship between the thickness of the stator yoke, the thickness of the rotor yoke, the relative magnet span of the motor and the motor power density using the finite element simulation method. On this basis, a response surface model between the three parameters and the power density of the motor was established. Based on this model and a differential evolution algorithm, the motor was optimized and the power density was improve;finally, the optimization results were verified using the finite element simulation method. In addition, the optimization results showed that, when other structure parameters remain unchanged, there is an optimal combination of parameters that can maximize the motor's power density, including the thickness of the stator yoke, the thickness of the rotor yoke and relative magnet span of the motor.

关键词： response surface model permanent magnet synchronous motor power density differential evolution algorithm

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differential evolution and Markov chain Monte Carlo analyses of layer disorder in nanosheet ensembles using total scattering

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JOURNAL OF APPLIED CRYSTALLOGRAPHY 2018年第5期51卷 1437-1444页

作者： Metz, Peter C. Koch, Robert Misture, Scott T. Alfred Univ Kazuo Inamori Sch Engn Alfred NY 14802 USA

Assemblies of nanosheets are often characterized by extensive layer-position disorder. Coupled with the often minute coherent scattering domain size and relaxation of the nanosheet structure itself, unambiguous interpretation of X-ray and neutron scattering data from such materials is non-trivial. This work demonstrates a general approach towards refinement of layer-disorder information from atomic pair distribution function (PDF) data for materials that span the gap between turbostratism and ordered stacking arrangements. X-ray total scattering data typical of a modern rapid-acquisition PDF instrument are simulated for a hypothetical graphene-like structure using the program DIFFaX, from which atomic PDFs are extracted. Small 1 x 1 x 20 supercell models representing the stacking of discrete layer types are combined to model a continuous distribution of layer-position disorder. Models optimized using the differential evolution algorithm demonstrate improved fit quality over 75 angstrom when a single mean layer-type model is replaced with a constrained 31-layer-type model. Posterior distribution analyses using the Markov chain Monte Carlo algorithm demonstrate that the influence of layer disorder and finite particle size are correlated. However, the refined mean stacking vectors match well with the generative parameter set.

关键词： pair distribution functions stacking disorder differential evolution algorithm Markov chain Monte Carlo algorithm nanosheets

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Evidential uncertainty quantification of the Park-Ang damage model in performance based design

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ENGINEERING COMPUTATIONS 2018年第7期35卷 2480-2501页

作者： Tang, Hesheng Li, Dawei Deng, Lixin Xue, Songtao Tongji Univ State Key Lab Disaster Reduct Civil Engn Shanghai Peoples R China Tongji Univ Res Inst Struct Engn & Disaster Reduct Shanghai Peoples R China

Purpose This paper aims to develop a comprehensive uncertainty quantification method using evidence theory for Park-Ang damage index-based performance design in which epistemic uncertainties are considered. Various sources of uncertainty emanating from the database of the cyclic test results of RC members provided by the Pacific Earthquake Engineering Research Center are taken into account. Design/methodology/approach In this paper, an uncertainty quantification methodology based on evidence theory is presented for the whole process of performance-based seismic design (PBSD), while considering uncertainty in the Park-Ang damage model. To alleviate the burden of high computational cost in propagating uncertainty, the differential evolution interval optimization strategy is used for efficiently finding the propagated belief structure throughout the whole design process. Findings The investigation results of this paper demonstrate that the uncertainty rooted in Park-Ang damage model have a significant influence on PBSD design and evaluation. It might be worth noting that the epistemic uncertainty present in the Park-Ang damage model needs to be considered to avoid underestimating the true uncertainty. Originality/value This paper presents an evidence theory-based uncertainty quantification framework for the whole process of PBSD.

关键词： differential evolution algorithm Epistemic uncertainty Evidence theory Park-Ang damage model Performance-based seismic design

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