Debin Fang

An improved artificial bee colony algorithm for solving constrained optimization problems

The artificial bee colony (ABC) algorithm is a global stochastic optimization algorithm inspired by simulating the foraging behavior of honey bees. It has been successfully applied to solve the constrained optimization problems (COPs) with a constraint handling technique (Deb’s rules). However, it may also lead to premature convergence. In order to improve this problem, we propose an improved artificial bee colony (I-ABC) algorithm for COPs. In I-ABC algorithm, we firstly relax the Deb’s rules by introducing the approximate feasible solutions to suitably utilize the information of the infeasible solutions with better objective function value and small violation. Next, we construct a selection strategy based on rank selection and design a search mechanism using the information of the best-so-far solution to balance the exploration and the exploitation at different stages. In addition, periodic boundary handling mode is used to repair invalid solutions. To verify the performance of I-ABC algorithm, 24 benchmark problems are employed and two comparison experiments have been carried out. The numerical results show that the proposed I-ABC algorithm has an outstanding performance for the COPs.

Solving the logit-based stochastic user equilibrium problem with elastic demand based on the extended traffic network model

This paper proposes a novel extended traffic network model to solve the logit-based stochastic user equilibrium (SUE) problem with elastic demand. In this model, an extended traffic network is established by properly adding dummy nodes and links to the original traffic network. Based on the extended traffic network, the logit-based SUE problem with elastic demand is transformed to the SUE problem with fixed demand. Such problem is then further converted to a linearly constrained convex programming and addressed by a predictor–corrector interior point algorithm with polynomial complexity. A numerical example is provided to compare the proposed model with the method of successive averages (MSA). The numerical results indicate that the proposed model is more efficient and has a better convergence than the MSA.

A solution approach to the weak linear bilevel programming problems

In this paper, we study the weak linear bilevel programming problems. For such problems, under some conditions, we first conclude that there exists a solution which is a vertex of the constraint region. Based on the classical Kth-Best algorithm, we then present a solution approach. Finally, an illustrative example shows that the proposed approach is feasible.

Bayesian Nash equilibrium bidding strategies for generation companies

With the reform of the electric power system and the development of generation power market in China, it is of significance to develop bidding strategies for generators. Bidding strategy is the profile of bidding price and bidding quantities, which is submitted by market participants, and auctioneer determines a rule to allocate the aggregate demand quantity among all generators, regarded as auction problem with divisible object. This paper describes discriminating pricing auction rule with divisible object auction, builds the Bayesian game model of the divisible object auction under the generators private cost information. Moreover, we resolve Nash equilibrium of a Bayesian game, transform Nash equilibrium of a Bayesian game as Nash equilibrium of the strategic game, with regarding marginal cost as the type of players, and get bidders bidding strategy under a certain marginal cost function of bidder.

Stochastic Evolution Dynamic of the Rock-Scissors-Paper Game Based on a Quasi Birth and Death Process.

Stochasticity plays an important role in the evolutionary dynamic of cyclic dominance within a finite population. To investigate the stochastic evolution process of the behaviour of bounded rational individuals, we model the Rock-Scissors-Paper (RSP) game as a finite, state dependent Quasi Birth and Death (QBD) process. We assume that bounded rational players can adjust their strategies by imitating the successful strategy according to the payoffs of the last round of the game, and then analyse the limiting distribution of the QBD process for the game stochastic evolutionary dynamic. The numerical experiments results are exhibited as pseudo colour ternary heat maps. Comparisons of these diagrams shows that the convergence property of long run equilibrium of the RSP game in populations depends on population size and the parameter of the payoff matrix and noise factor. The long run equilibrium is asymptotically stable, neutrally stable and unstable respectively according to the normalised parameters in the payoff matrix. Moreover, the results show that the distribution probability becomes more concentrated with a larger population size. This indicates that increasing the population size also increases the convergence speed of the stochastic evolution process while simultaneously reducing the influence of the noise factor.

Discovering research topics from library electronic references using latent Dirichlet allocation

Discovering the research topics and trends from a large quantity of library electronic references is essential for scientific research. Current research of this kind mainly depends on human justification. The purpose of this paper is to demonstrate how to identify research topics and evolution in trends from library electronic references efficiently and effectively by employing automatic text analysis algorithms.,The authors used the latent Dirichlet allocation (LDA), a probabilistic generative topic model to extract the latent topic from the large quantity of research abstracts. Then, the authors conducted a regression analysis on the document-topic distributions generated by LDA to identify hot and cold topics.,First, this paper discovers 32 significant research topics from the abstracts of 3,737 articles published in the six top accounting journals during the period of 1992-2014. Second, based on the document-topic distributions generated by LDA, the authors identified seven hot topics and six cold topics from the 32 topics.,The topics discovered by LDA are highly consistent with the topics identified by human experts, indicating the validity and effectiveness of the methodology. Therefore, this paper provides novel knowledge to the accounting literature and demonstrates a methodology and process for topic discovery with lower cost and higher efficiency than the current methods.

An interactive intuitionistic fuzzy method for multilevel linear programming problems

In this paper, we propose an interactive method for solving the multilevel linear programming problems based on the intuitionistic fuzzy set theory. Firstly, the membership function and the non-membership function are introduced to describe the uncertainty of the decision makers. Secondly, a satisfactory solution is derived by updating the minimum satisfactory degrees with considerations of the overall satisfactory balance among all levels. In addition, the steps of the proposed method are given in this paper. Finally, numerical examples illustrate the feasibility of this method.

Power coal transportation and storage: A programming analysis of road and rail options

In this study, the transportation and storage problems for regional power coal allocation planning are formulated as transportation and storage problems to realize the minimization of the regional transportation and storage cost. An effective optimization model is proposed to solve transportation and storage problems for regional power coal allocation planning, which has interactive effect on multiple participants, such as regional power plants, coal transportation companies, logistics centers, and coal storage centers. A case study illustrates that the model and algorithm are more reasonable compared with the classic transportation model, and the sensitivity analysis improves transportation and storage strategies for regional power coal allocation planning. Results demonstrate that this model can not only satisfy more of the actual requirements of the integral system but also offer more information to the decision-makers (DMs) for reference in favor of exalting decision-making quality.

The Extensive Game Model of Electric Power Transaction between Generator and Large Customer

This paper studies market behaviors that generation company supplies electricity to large customer directly, describes pricing strategies for the generation companies in the large customers purchase electricity directly, models electricity bargaining between generation and large customer, resolves equilibrium strategies and subgame perfect equilibrium, discusses exhaustively characteristics of equilibrium to provide decision support for generation companies and large customer

Intelligent bid decision support system for generation companies

With the progress of transmission and power plant separation and competition before supply, generation companies are anxious to have an efficient bidding assistant decision system to gain more benefit. Intelligent bid decision support system for generation companies (GCBIDSS) is a computer system to assist generation companies to price the electricity. This paper introduces the conception of intelligent decision support system (IDSS), and puts emphasis on the systematical structural framework, work process, design principal, and fundamental function of GCBIDSS. The case study illustrates that the friendly window-based user interface of the system enables the user to take full advantage of the capabilities of the system in order to make effective real-time decision.