The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
A multi-objective evolutionary algorithm with extended minimal generation gap (MGG) model and distance-based density measure is given, which we call DMOEA. DMOEA employs a new technique to estimate the distance between two individuals in the objective space, further, finds the K nearest neighbors on either side of certain individual along one focused objective, calculates the sum of the distances...
This paper is mainly devoted to identify an evolutionary approach based on search strategy, namely multiobjective evolutionary algorithm for indoor positioning (MEIP). Each subproblem is optimized by information from its several neighboring subproblems, which makes MEIP lower computational complexity at each generation and be capable of determining the user position with high accuracy. Experimental...
Niche genetic algorithm (NGA) is superior to genetic algorithm (GA) in multiple hump function optimization. NGA could search all global optimums of multiple hump function in a running. It is a class of parallel evolutionary method which suppresses genetic drift by forming stable subpopulations to maintain population diversity. To algorithm population diversity plays an important role to avoid trapping...
This paper proposes a new evolution algorithm, M_GEP, based on the concept of multi-gene chromosome in gene expression programming. The algorithm has two characters: (1) a chromosome is composed of more than one gene; (2) the sub-genes are linked together according to the linking gene which may conclude more than one kind of function. We give two examples, whose results show that the models set up...
Based on the perfect rationality and common knowledge theoretically hypotheses, the out-of-equilibrium outcome or out of subgame perfect equilibrium path couldn't achieve in traditional game theory. Evolutionary game theory analyzes the population's dispersive behaviors under the bounded rational hypothesis. The theoretical payoffs of different strategies are decided by the practical observed outcome,...
Genetic operators play an important role in Evolution Strategies (ES). There are two important issues in the evolution process of the genetic search: exploration and exploitation. We analyze the impact of the genetic operators in ES. The Classical Evolution Strategies (CES) relies on Gaussian mutation, whereas Fast Evolution Strategies (FES) selects Cauchy distribution as the primary mutation operator...
The famous Todaro model could not explain the circulative flowed phenomenon in the course of rural labor transfer. The paper uses Sethi's generic replicator dynamic model (1998) of evolutionary game theory to explain the circulative flowed phenomenon based Chinese statistical data. It builds the urban-rural ternary-structure model including rural section, urban informal section and urban formal section,...
Multi-objective optimization problems (MOPs) in real world are often constrained optimization problems. So test problems to evaluate multi-objective optimization evolutionary algorithms (MOEAs) should have some constraints in order to simulate real-world problems. In this paper, a well understood and tunable constrained test problems generator is suggested. By setting parameters in the constraint...
Transportation network design problem deals with how to add or improve some edges on an existing transportation network to improve traffic condition. In this study a bi-level programming model was proposed to optimize the strategy of transportation network capacity improvement in the constraint of budget. The upper level problem aims to minimize the total travel time of all transportation travelers,...
Computer worms evolved continually, faster and smarter. Proactive P2P worms with new "gene" propagate over logical P2P overlay networks defined by peer relationship. Observations suggest that the node degrees of an unstructured P2P network are power law distributed thus we model it as a power law undirected graph. We study propagation process of proactive P2P worm using a dynamic epidemic...
In this paper, we propose a new multi-objective optimization approach based the clonal selection principle which is from an artificial immune system. Our approach uses the cluster method in the memory cell set of the clonal selection principle to renew and eliminate antibody; the non-uniform mutation operator is employed to the multiplicity of population. This algorithm cannot promote to individual...
This paper proposes a new chaotic hybrid cultural algorithm to solve constrained optimization problems. In the proposed method, differential evolution is embedded into cultural algorithm as its population space and applies situational and normative knowledge sources in belief space to influence the variation operator of differential evolution. We apply chaos theory to obtain self-adaptive parameter...
This paper proposes an enhanced cultural algorithm to solve the profit-based optimal self-scheduling of a hydro producer in the electricity market. In the proposed method, differential evolution is embedded into cultural algorithm as its population space and situational and normative knowledge sources in belief space are applied to influence the variation operator of differential evolution. Furthermore,...
This paper presents a hybrid evolutionary algorithm to solve mixed-integer nonlinear bilevel programming problems, in which integer decision variables are controlled by an upper-level decision maker and real-value (continuous) decision variables are controlled by a lower-level decision maker. This hybrid evolutionary algorithm contains the mutation operator used in the differential evolution, the...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.