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Abstract: Ecological expert knowledge is often based on qualitative rules consisting of linguistic terms such as ‘low’, ‘moderate’ or ‘high’. Since fuzzy systems transform these rules and terms into a mathematical framework, they allow implementing this expert knowledge in ecological models. However, the development of a reliable knowledge base is complex and time consuming. Recent research has shown that complementing fuzzy systems by data-driven techniques can solve this knowledge acquisition bottleneck. In this paper, a heuristic nearest ascent hill-climbing algorithm for rule base optimisation is applied to construct a fuzzy rule-based habitat suitability model for spawning European grayling (Thymallus thymallus L.) in the Aare river (Bern, Switzerland). Optimisation of the fuzzy rule-based model was based on two different training criteria, the weighted correctly classified instances and Cohen''s Kappa. The ecological relevance of the results was assessed by comparing the optimised rule bases with a rule base derived from ecological expert knowledge. Optimisation based on Kappa appeared to generate acceptable results (CCI=0.70; Kappa=0.32) and was more practical than optimisation based on since the latter required fine tuning of a weight parameter, which accounted for the species prevalence. The optimal rules showed 74% similarity with the rules derived from expert knowledge, while 84% of all model errors was due to false positive predictions of the model. These errors might be due to the impact of variables, which were not included in this study on grayling presence and thus are not necessarily a model error. The habitat suitability model optimised in this paper is able to predict the effect of different impacts on the river system and to select the optimal restoration option. Hence, it could be a valuable decision support tool for river managers and ease the discussion between stakeholders. [Copyright &y& Elsevier]

Abstract: A rank-niche evolution strategy (RNES) algorithm has been developed in this paper to solve unconstrained multiobjective optimization problems. A required number of Pareto-optimal solutions can be generated by the algorithm in a single run. In addition to the operations of recombination, mutation and selection used in original evolution strategy (ES), an external elite set which contains a given number of non-dominated elites is updated and trimmed by a clustering technique to maintain a uniformly distributed Pareto front. The fitness function for each individual contains the information of rank and crowding status. The selection operation using this fitness function considers the superiority and distribution simultaneously. Eight test problems illustrated in other papers are used to test RNES. For some test problems the Pareto-optimal solutions obtained by RNES are better than those obtained by GA-based algorithms. [Copyright &y& Elsevier]

Abstract: In this paper, we consider a class of non-standard time optimal control problems involving a dynamical system consisting of multiple subsystems evolving over different time horizons. Different subsystems are required to reach their respective target sets at different termination times. The goal is to minimize the maximum of these termination times. By introducing a discrete variable to represent the system termination ordering, we reformulate this problem as a discrete optimization problem. A discrete filled function method is developed to solve this discrete optimization problem. For illustration, a numerical example is solved. [Copyright &y& Elsevier]

Abstract: In this paper, we use the third order shear deformation theory of Reddy [Reddy JN. Mechanics of laminated composite plates and shells. CRC Press; 2004] with a meshless numerical method to analyze the static deformation of composite plates and shells. Numerical results are compared with Navier solutions in various examples. The meshless collocation method based on radial basis functions requires a user-defined shape parameter than can compromise the quality of the solution when poorly chosen. To improve the choice of this shape parameter, we apply an optimization technique based on the leave-one-out cross validation analysis to obtain the shape parameter in a given interval. The results obtained were significantly better than those produced with a user-defined shape parameter. [Copyright &y& Elsevier]

Abstract: The aim of the paper is to report a systematic methodology which is used to evaluate and improve the ride comfort. An accurate model is necessary for further investigation and optimization. The vehicle dynamics model of tractor with tandem suspension is modeled and simulated in dynamics software ADAMS, which is redeveloped to add a function of automatic parametric modeling and simulation. The modeling methods of nonlinear characteristic components and various road excitation inputs, which can be simply seen as the implementation means for the model solution, are introduced. A new index called annoyance rate is presented to indicate the quantitative correlation between objective method and subjective comment. The quantitative correlation between them, which is quite different from the qualitative “comfortable” or “uncomfortable” results attained by objective evaluation, can be defined by function and regarded as a basis to scientifically evaluate and improve the ride comfort. According to the request of performance-based design, the parameter sensitive analysis and structure optimization have been carried out to find the trade-off among ride comfort, maneuverability and safety. The approach has proved to be very effective for predicting and improving the ride comfort by experiment results. The methodology can be also used for any other specific category of vehicle. [Copyright &y& Elsevier]

Abstract: In this paper we propose a generic methodology for the automated generation of fuzzy models. The methodology is realized in three stages. Initially, a crisp model is created and in the second stage it is transformed to a fuzzy one. In the third stage, all parameters entering the fuzzy model are optimized. The proposed methodology is novel and generic since it can integrate alternative techniques in each of its stages. A specific realization of this methodology is implemented, using decision trees for the creation of the crisp model, the sigmoid function, the min–max operators and the maximum defuzzifier, for the transformation of the crisp model into a fuzzy one, and four different optimization strategies, including global and local optimization techniques, as well as, hybrid approaches. The proposed methodology presents several advantages and novelties: the transformation of the crisp model to the respective fuzzy one is straightforward ensuring its full automated nature and it introduces a set of parameters, expressing the importance of each fuzzy rule. The above realization is extensively evaluated using several benchmark data sets from the UCI machine learning repository and the obtained results indicate its high efficiency. [Copyright &y& Elsevier]

Abstract: Differential evolution (DE) is a heuristic method that has yielded promising results for solving complex optimization problems. The potentialities of DE are its simple structure, easy use, convergence property, quality of solution, and robustness. This paper utilizes a DE strategy to parameters estimation of structural systems, which could be formulated as a multi-modal numerical optimization problem with high dimension. Simulation results for identifying the parameters of structural systems under conditions including limited output data, noise polluted signals, and no prior knowledge of mass, damping, or stiffness are presented to demonstrate the effectiveness of the proposed method. [Copyright &y& Elsevier]

Abstract: Optimization design is the most important key technique of Air-breathing Hypersonic Cruise Vehicle (HCV). To improve the design level and get better integrated performances of HCV, this paper researches the integrated optimization design method of waverider hypersonic cruise vehicle. In the optimization design, Multi-Objective Genetic Algorithms (MOGA) is selected as the optimization algorithm, and the shape parameters of aircraft are as design variables. Some performances, such as aerodynamics, aeroheating, radar cross section (RCS), airframe/scramjet integration, and volume of airframe, trimmed characteristic, static stability and maneuverability at cruise phase are selected as the objectives. When the optimization process finishes, the Pareto front side is got, in which many Pareto solutions whose integrated performances are more excellent than basic configuration are found. According to the design idea, we choose a Pareto solution from the Pareto front side as the recommended shape configuration for further research. To validate the aerodynamics of recommended configuration, wind tunnel test is done. And the comparison results show that the optimization design is successful. [Copyright &y& Elsevier]

Abstract: Bilevel programming has been proposed for dealing with decision processes involving two decision makers with a hierarchical structure. They are characterised by the existence of two optimisation problems in which the constraint region of the upper level problem is implicitly determined by the lower level optimisation problem. In this paper we focus on the class of bilevel problems in which the upper level objective function is linear multiplicative, the lower level one is linear and the common constraint region is a bounded polyhedron. After replacing the lower level problem by its Karush–Kuhn–Tucker conditions, the existence of an extreme point which solves the problem is proved by using a penalty function approach. Besides, an algorithm based on the successive introduction of valid cutting planes is developed obtaining a global optimal solution. Finally, we generalise the problem by including upper level constraints which involve both level variables. [Copyright &y& Elsevier]

Abstract: This paper deals with a special case of multicriteria optimization problems. The problems studied come from the medical domain and are of a very important practical relevance. One of the problems refers to the ranking of treatments for the Trigeminal Neuralgia. The second problem refers to a hierarchy of risk factors for Bronchial Asthma. The most common way to deal with a multiobjective optimization problem is to apply Pareto dominance relationship between solutions. But in the cases studied here, a decision cannot be made just by using Pareto dominance. In one of the experiments, all the potential solutions are nondominated (and we need to clearly find a hierarchy of these solutions) and in the second experiment most of the solutions are nondominated between them. We propose a novel multiple criteria procedure and then an evolutionary scheme is applied for solving the problems. Results obtained by the proposed approach in a very simple way are same as the results (or even better) obtained by applying weighted-sum method. The advantage of the proposed technique is that it does not require any additional information about the problem (like weights for each criteria in the case of weighted-sumapproach). [Copyright &y& Elsevier]

Abstract: Image registration algorithms rely on multilevel strategies in order to improve efficiency and robustness. Hierarchies in image resolution, the underlying grids for spline-based transformations, as well as the regularisation parameters are used. This paper deals with the optimisation of the coupling of these hierarchies. An image registration procedure – suitable for 2D polyacrylamide gel electrophoresis images – using piecewise bilinear transformations and an intensity based objective function with a regularisation term based on the elastic deformation energy is described. The resulting nonlinear least squares problem is solved by the Gauss–Newton method. Techniques reminiscent of dynamic programming are used to optimise the coupling of hierarchies in image and transformation resolution. Besides using these techniques to devise an advantageous fixed coupling of both hierarchies, we favour incorporating the dynamic programming ideas into the final registration algorithm. This leads to an adaptive and streamlined approach. Numerical experiments on 2D-PAGE images show that the adaptive registration algorithm is much more reliable than the same algorithm with a fixed coupling of hierarchies. The proposed optimisation procedure for the coupling of hierarchies presents a valuable tool to optimise other registration algorithms. [Copyright &y& Elsevier]

Abstract: In this paper, a new image segmentation technique called WaterBalloons is introduced. It combines both watershed segmentation and the active contour model known as Balloon Snake. The watershed transform has a major problem of over-segmentation. Solutions like region merging, use of markers, use of multi-scales have been proposed. These approaches led to other problems such as under-segmentation. The Balloon Snake in an innovative approach that detects salient objects in an image. But in general snakes are very sensitive to initialization and need user interactions and a priori knowledge of objects to segment. WaterBalloons provide the advantage of reducing watershed over-segmentation problems while preventing under-segmentation and ensure automatic initialization of traditional snakes. In addition, a method for parameter optimization of the proposed hybrid snake is introduced based on energy transitions tracking. [Copyright &y& Elsevier]

Abstract: The splitting spinning which is designed to split a rotational disk blank into two flanges, is one of newly rising, green flexible forming technologies, and it can be widely applied to manufacture a whole pulley or wheel in fields of aerospace, automobile and train. The investigation of forming parameters influencing on splitting spinning force can provide the foundation for the choice of equipments, the design of dies and the determination of processing parameters. This paper aims at developing a reasonable formula between splitting spinning force and forming parameters by the principal stress method, and then the reliability of the formula is verified by the comparisons with experimental data. Meanwhile, both a reasonable method of calculating the three-dimensional projected areas and a more effective method of solving the average angle in the deformation zone are presented. Furthermore, based on the formula, the laws of initial thickness and initial diameter of workpiece, diameter and splitting angle of splitting roller and feed ratio of splitting spinning influencing on splitting spinning force are investigated. The achievements may serve as an important guide for the determination and optimization of forming parameters of splitting spinning. [Copyright &y& Elsevier]

Abstract: Cold cross-wedge rolling process is utilized to enhance the surface hardness and the strength in a round shaped part. Main geometrical design parameters in a cold cross-wedge rolling die are the forming angle, the spreading angle, and the die height. General defects in this process are an excessive slip on the surface and a hole generation at the center point which is usually called as the Mannesmann hole defect. The friction coefficient and geometrical design variables affect occurrences of an excessive slip and/or a central hole generation. In this paper, effects of the forming angle and the friction coefficient on the initiation of the Mannesmann hole defect are analyzed by using a response surface method. Integrals of four different ductile fracture models are compared with a history of the effective plastic strain at the central point. It reveals that the maximum effective plastic strain at the point can be utilized to determine the initiation point of the ductile fracture in the cold cross-wedge rolling process. Optimization of design parameters for prevention of the Mannesmann hole defect initiation is carried out using a response surface method. As results, that the forming angle of 25° and the spreading angle of 1° can be proper design conditions with the prevention of occurrences of internal hole defect and an excessive slip. Optimum design specification is testified by the experimental result. [Copyright &y& Elsevier]

Abstract: In this paper, we introduce a new genetic representation — a splicing/decomposable (S/D) binary encoding, which was proposed based on some theoretical guidance and existing recommendations for designing efficient genetic representations. The S/D binary representation can be spliced and decomposed to describe potential solutions of the problem with different precisions by different number of uniform-salient building blocks (BBs). According to the characteristics of the S/D binary representation, genetic and evolutionary algorithms (GEAs) can be applied from the high scaled to the low scaled BBs sequentially to avoid a noise from the competing BBs and improve GEAs’ performance. Our theoretical and empirical investigations reveal that the S/D binary representation is more proper than other existing binary encodings for GEAs searching. Moreover, we define a new genotypic distance on the S/D binary space, which is equivalent to the Euclidean distance on the real-valued space during GEAs convergence. Based on the new genotypic distance, GEAs can reliably and predictably solve problems of bounded complexity and the methods depended on the Euclidean distance for solving different kinds of optimization problems can be directly used on the S/D binary space. [Copyright &y& Elsevier]

Abstract: This paper studies maximality and totality of stable functions in the category of stable bifinite domains. We present three main results as follows, [o] [(1)] every maximum-preserving function is a maximal element in the stable function spaces; [(2)] a maximal stable function f : D → E is maximum-preserving if D is maximum-separable and E is completely separable; and [(3)] a stable bifinite domain D is maximum-separable if and only if for any locally distributive stable bifinite domain E, each maximal stable function f : D → E is maximum-preserving. [Copyright &y& Elsevier]

Abstract: This paper considers the mixed sensitivity optimization problem for a class of infinite-dimensional stable plants. This problem is reducible to a two- or one-block control problem with structured weighting functions. We first show that these weighting functions violate the genericity assumptions of existing Hamiltonian-based solutions such as the well-known Zhou–Khargonekar formula. Then, we derive a new closed form formula for the computation of the optimal performance level, when the underlying plant structure is specified by a pseudorational transfer function. [Copyright &y& Elsevier]

Abstract: In this paper the possibility of including automatic optimization techniques in the design of parallel dynamic programming algorithms in heterogeneous systems is analyzed. The main idea is to automatically approach the optimum values of a number of algorithmic parameters (number of processes, number of processors, processes per processor), and thus obtain low execution times. Hence, users could be provided with routines which execute efficiently, and independently of the experience of the user in heterogeneous computing and dynamic programming, and which can adapt automatically to a new network of processors or a new network configuration. [Copyright &y& Elsevier]

Abstract: In this paper, a mathematical program with complementarity constraints (MPCC) is reformulated as a nonsmooth constrained optimization problem by using the Fischer–Burmeister function. An augmented (proximal) Lagrangian method is applied to tackle the resulting constrained optimization problem. The augmented Lagrangian problems are in general nonsmooth. We derive first- and second-order optimality conditions for the augmented Lagrangian problems using an approximate smooth variational principle and establish that the limit point of a sequence of points that satisfy the second-order necessary optimality conditions of the augmented Lagrangian problems is a strongly stationary point of the original MPCC if the limit point is feasible to MPCC, and the linear independence constraint qualification for MPCC and the upper level strict complementarity condition hold at the limit point. [Copyright &y& Elsevier]