Multiobjective Decision Making: the Combined Approach

: In this paper, a new approach for generating all or partly efficient solutions called the Combined Approach is developed. The property of efficient solutions generated by the combined approach and its relationships with other four approaches: weighting approach, sequential approach, ε-constraint approach and hybrid approach, are discussed. Based on this combined approach, a decision-making support method called the Combined Decision-Making Method (CDMM) for multiobjective problems is developed, which is an interactive process with the decision maker. Only the aspiration levels, which reflect the decision maker's satisfying degrees for corresponding objectives, are needed to be supplied by the decision maker step by step as he will. This interactive way for objectives can easily be accepted. Finally, the application of the proposed decision making method in the resource allocation problem is discussed, and an example for the production decision analysis of the solar energy cells given.     

Face Recognition Based on Support Vector Machine and Nearest Neighbor Classifier

Support vector machine (SVM), as a novel approach in pattern recognition, has demonstrated a success in face detection and face recognition. In this paper, a face recognition approach based on the SVM classifier with the nearest neighbor classifier (NNC) is proposed. The principal component analysis (PCA) is used to reduce the dimension and extract features. Then one-against-all stratedy is used to train the SVM classifiers. At the testing stage, we propose an al-     

SIMPLE COMPUTING OF THE CUSTOMER LIFETIME VALUE:A FIXED LOCAL-OPTIMAL POLICY APPROACH

In this paper,we present a new method for finding a fixed local-optimal policy for computing the customer lifetime value.The method is developed for a class of ergodic controllable finite Markov chains.We propose an approach based on a non-converging state-value function that fluctuates（increases and decreases） between states of the dynamic process.We prove that it is possible to represent that function in a recursive format using a one-step-ahead fixed-optimal policy.Then,we provide an analytical formula for the numerical realization of the fixed local-optimal strategy.We also present a second approach based on linear programming,to solve the same problem,that implement the c-variable method for making the problem computationally tractable.At the end,we show that these two approaches are related：after a finite number of iterations our proposed approach converges to same result as the linear programming method.We also present a non-traditional approach for ergodicity verification.The validity of the proposed methods is successfully demonstrated theoretically and,by simulated credit-card marketing experiments computing the customer lifetime value for both an optimization and a game theory approach.     

Hybrid hierarchical trajectory planning for a fixed-wing UCAV performing air-to-surface multi-target attack

This paper considers the problem of generating a flight trajectory for a single fixed-wing unmanned combat aerial vehicle (UCAV) performing an air-to-surface multi-target attack (A/SMTA) mission using satellite-guided bombs. First, this problem is formulated as a variant of the traveling salesman problem (TSP), called the dynamic-constrained TSP with neighborhoods (DCTSPN). Then, a hierarchical hybrid approach, which partitions the planning algorithm into a roadmap planning layer and an optimal control layer, is proposed to solve the DCTSPN. In the roadmap planning layer, a novel algorithm based on an updatable probabilistic roadmap (PRM) is presented, which operates by randomly sampling a finite set of vehicle states from continuous state space in order to reduce the complicated trajectory planning problem to planning on a finite directed graph. In the optimal control layer, a collision-free state-to-state trajectory planner based on the Gauss pseudospectral method is developed, which can generate both dynamically feasible and optimal flight trajectories. The entire process of solving a DCTSPN consists of two phases. First, in the offline preprocessing phase, the algorithm constructs a PRM, and then converts the original problem into a standard asymmetric TSP (ATSP). Second, in the online querying phase, the costs of directed edges in PRM are updated first, and a fast heuristic searching algorithm is then used to solve the ATSP. Numerical experiments indicate that the algorithm proposed in this paper can generate both feasible and near-optimal solutions quickly for online purposes.     

Target aggregation of second-order multi-agent systems with switching interconnection

In this paper,the target aggregation is investigated for a multi-agent system consisting of second-order agents and multiple leaders.Sufficient conditions are proposed to make the agents approach the target set spanned by these moving leaders.With the condition on switching interconnection topologies,all mobile agents can asymptotically track the dynamical target set specified by multiple moving leaders with bounded error.Moreover,discussion on the case with static leaders is also given.     

H 2/H ∞ control problems of backward stochastic systems

This paper is concerned with the mixed H2/H∞ control problem for a new class of stochastic systems with exogenous disturbance signal.The most distinguishing feature,compared with the existing literatures,is that the systems are described by linear backward stochastic differential equations（BSDEs）.The solution to this problem is obtained completely and explicitly by using an approach which is based primarily on the completion-of-squares technique.Two equivalent expressions for the H2/H∞ control are presented.Contrary to forward deterministic and stochastic cases,the solution to the backward stochastic H2/H∞ control is no longer feedback of the current state;rather,it is feedback of the entire history of the state.     

Delay-dependent robust H∞ control of convex polyhedral uncertain fuzzy systems

The robust H∞ control problem for a class of uncertain Takagi-Sugeno fuzzy systems with timevarying state delays is studied. The uncertain parameters are supposed to reside in a polytope. Based on the delay-dependent Lyapunov functional method, a new delay-dependent robust H∞ fuzzy controller, which depends on the size of the delays and the derivative of the delays, is presented in term of linear matrix inequalities （LMIs）. For all admissible uncertainties and delays, the controller guarantees not only the asymptotic stability of the system but also the prescribed H∞ attenuation level. In addition, the effectiveness of the proposed design method is demonstrated by a numerical example.     

A MARKOVIAN APPROACH TO DETERMINING PROCESS MEANS WITH DUAL QUALITY CHARACTERISTICS

This paper studies a production system where products are produced continuously and whose specification limits are specified for screening inspection. In this paper, we consider dual quality characteristics and different costs associated with each quality characteristic that falls below a lower specification limit or above an upper specification limit. Due to these different costs, the expected total profit will greatly depend on the process parameters, especially a process mean. This paper develops a Markovian-based model for determining the optimum process means with the consideration of dual quality characteristics in a single-stage system. The proposed model is then illustrated through a numerical example and sensitivity analysis is performed to validate the model. The results showed that the optimum process mean for both quality characteristics have a significant effect on the performance of the system. Since the literature survey shows that dealing with multi-quality characteristics is extremely limited, the proposed model, coupled with the Markovian approach, provides a unique contribution to this field.     

Bayesian estimation for nonlinear stochastic hybrid systems with state dependent transitions

The Bayesian approach is considered as the most general formulation of the state estimation for dynamic systems.However,most of the existing Bayesian estimators of stochastic hybrid systems only focus on the Markov jump system,few literature is related to the estimation problem of nonlinear stochastic hybrid systems with state dependent transitions.According to this problem,a new methodology which relaxes quite a restrictive assumption that the mode transition process must satisfy Markov properties is proposed.In this method,a general approach is presented to model the state dependent transitions,the state and output spaces are discreted into cell space which handles the nonlinearities and computationally intensive problem offline.Then maximum a posterior estimation is obtained by using the Bayesian theory.The efficacy of the estimator is illustrated by a simulated example.     

Convergence rates of Markov chain approximation methods for controlled diffusions with stopping

<正> This work is concerned with rates of convergence of numerical methods using Markov chainapproximation for controlled diffusions with stopping (the first exit time from a bounded region).In lieuof considering the associated finite difference schemes for Hamilton-Jacobi-Bellman (HJB) equations,a purely probabilistic approach is used.There is an added difficulty due to the boundary condition,which requires the continuity of the first exit time with respect to the discrete parameter.To prove theconvergence of the algorithm by Markov chain approximation method,a tangency problem might arise.A common approach uses certain conditions to avoid the tangency problem.Here,by modifying thevalue function,it is demonstrated that the tangency problem will not arise in the sense of convergencein probability and in L~1.In addition,controlled diffusions with a discount factor is also treated.     

ON ACYCLIC AND CYCLIC HYPERGRAPHS

So far, the acyclic hypergraph has two different definitions. One is based on the cyclomatic number of the hypergraph, whereas the other arises from the acyclic schema of the relational database in the computer science. In this paper, it is first proved that these two definitions coincide with each other completely. Then we prove that a hypergraph H is not acyclic, or cyclic, if and only if it contains a special partial hypergraph named hypercircuit. In addition, we show that H has l(H) different hypercircuits, where l(H) is a parameter used to decide whether H is acyclic or cyclic.     

Fractional Order Iteration for Gradient Descent Method Based on Event-Triggered Mechanism

In this work, a novel gradient descent method based on event-triggered strategy has been proposed, which involves integer and fractional order iteration. Firstly, the convergence of integer order iterative optimization method and the stability of its associated system with integrator dynamics are linked. Based on this result, a fractional order iteration approach has been developed by modelling the system with fractional order dynamics. Secondly, to reduce the comsumption of computation, a feedb...     

UNIFORM PERSISTENCE AND GLOBAL ATTRACTIVITY FOR NONAUTONOMOUS COMPETITIVE SYSTEMS WITH DISPERSION

In this paper, we consider a nonautonomous competitive model with dispersion and a finite number of discrete delays. The system, which consists of two Lotka-Volterra patches, has two competitors: one can disperse between the two patches, but the other is confined to one patch and cannot disperse. Our purpose is to demonstrate that the dispersion rates have no effect on the uniform persistence of the solutions of the system. Furthermore, we establish the conditions under which the system admits a positive periodic solution which attracts all solutions.     

On parametric approach of aerial robots' visual navigation

In aerial robots＇ visual navigation, it is essential yet very difficult to detect the attitude and position of the robots operated in real time. By introducing a new parametric model, the problem can be reduced from almost unmanageable to be partly solved, though not fully, as per the requirement. In this parametric approach, a multi-scale least square method is formulated first. By propagating as well as improving the parameters down from layer to layer of the image pyramid, a new global feature line can then be detected to parameterize the attitude of the robots. Furthermore, this approach paves the way for segmenting the image into distinct parts, which can be realized by deploying a Bayesian classifier on the picture cell level. Comparison with the Hough transform based method in terms of robustness and precision shows that this multi-scale least square algorithm is considerably more robust to noises. Some discussions are also given.     

The Invertibility of Rational Univariate Representations

In this paper, the so-called invertibility is introduced for rational univariate representations, and a characterization of the invertibility is given. It is shown that the rational univariate representations, obtained by both Rouillier’s approach and Wu’s method, are invertible. Moreover, the ideal created by a given rational univariate representation is defined. Some results on invertible rational univariate representations and created ideals are established. Based on these results, a new appr...     

Finite-time tracking control for motor servo systems with unknown dead-zones

A finite-time tracking control scheme is proposed in this paper based on the terminal slid- ing mode principle for motor servo systems with unknown nonlinear dead-zone inputs. By using the differential mean value theorem, the dead-zone is represented as a time-varying system and thus the inverse compensation approach is avoided. Then, an indirect terminal sliding mode control （ITSMC） is developed to guarantee the finite-time convergence of the tracking error and to overcome the singu- larity problem in the traditional terminal sliding mode control. In the proposed controller design, the unknown nonlinearity of the system is approximated by a simple sigmoid neural network, and the ap- proximation error is diminished by employing a robust term. Comparative experiments on a turntable servo system are conducted to show the superior performance of the proposed method.     

Kind of deadlock-free scheduling method

Deadlock must be avoided in a manufacturing system. In this paper, an efficient algorithm for finding an optimal deadlock-free schedules in a manufacturing system with very limited buffer is presented. This algorithm is based on the effective genetic algorithm (GA) search method, and a formal Petri net structure is introduced to detect the token player assuring deadlock-free. In order to make the scheduling strategy generated by GA meet the required constraint of deadlock-free, some results of the structure analysis of Petri net are involved as a criterion to select deadlock-free schedule from the population generated by GA. The effectiveness and efficiency of the proposed approach is illustrated by using an example.     

A novel mixed integer programming formulation and progressively stochastic search for capacitated lot sizing

The capacitated multi-level lot sizing problem is to schedule a number of different items with a bill-of-materials structure over a horizon of finite periods.To advance techniques of solving this class of problems,this paper proposes a new mixed integer programming formulation.Theoretical proofs and computational tests are provided to show that this formulation is able to provide better linear programming relaxation lower bounds than a previously-proposed strong mixed integer programming formulation.Based on the new strong formulation,a progressively stochastic search approach is proposed for solving the problem.Computational results showed that the approach generates high quality solutions,especially for problems of large sizes.     

COMPLEX ECO-ECONOMY SYSTEM

In the past there were a lot of researches on the topic of economic growth. Nevertheless, the environment has been a bit abstracted by standard economics. Scarce natural resources and our choices to protect them or exploit them jointly determine the economic and environmental systems. In this paper we describe a model with a particular focus on the relationship among income, pollution, and non-renewable resources. We want to combine both economic and environmental sectors. The system dynamics approach is used in analyzing these complex relationships. This paper gives an insight into the possibilities for replacing non-renewable resources with more renewable ones. Next, we present the simulation runs of the model that are conducted with the help of existing system dynamics modeling tools. Only the relationships simulated so far between the variables ought to be put under yet more cautious examination.