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Analysis of transient fluid flow in porous media has several applications in geophysics/geotechnics and engineering. An in-depth evaluation of fluid flow behavior is critical in order to improve the understanding, and development of, laboratory measurement techniques in geo-mechanics, particularly permeability estimation. Given that considerable errors may be yielded in the derived permeabilities of sorptive rocks when using the conventional pressure-pulse decay method (PDM), this paper proposes a new experimental design, an optimized PDM, by creating dual pressure pulses to avoid the pressure disturbance due to compressive storage, ad-/de-sorption and thermal effect during the course of measurement. In this paper, the first of a two-part series, a mathematical model established for the conventional PDM was modified to closely represent the new experimental design, thereby extending the transient technique for permeability measurement of unconventional reservoir rocks, particularly ones with large sorption potential. Considering the complexity of analytical solutions of mathematical models, a comprehensive numerical investigation was established and a detailed comparison was carried out between the conventional and optimized PDMs. The results showed how the profiles of the decay curves change in space and time domain, and how pressure responses are influenced by various parameters in the experimental design for PDM. Combining the new design with numerical simulation results in an optimized technique for fast and accurate permeability measurement of sorptive rocks. In particular, Brace et al.’s solution, the most acknowledged and commonly-used permeability calculation method, was extended for permeability estimation of sorptive rocks. In Part 2, the experimental work under best-replicated in situ stress/strain conditions using the optimized method along with the numerical pressure response results obtained from computer simulation is presented. The results verified the practicality of the optimized PDM and the validity of Brace et al.’s solution for permeability measurement of sorptive rocks. [ABSTRACT FROM AUTHOR]

Abstract: The paper's objective is to suggest a model for determining optimal lifetime of passenger car based on minimization of CO2 emission. The life cycle was modeled by eight main life cycle sequences. Combining the mathematical interpretations of the itch life cycle sequence is developed an optimization model. In this paper is suggested a new mathematical interpretation of following sequences: use, repair, distribution of passenger car and distribution of passenger car's parts. Comparison of the obtained numerical results was performed on examples for the data of new passenger car fleet from the EU14 countries. Special attention is given to analysis of dependencies between the optimal lifetime of passenger cars and Directive 2000/53/EC, trends of changing car weight, model year, kilometer driven and regulatory limit of the specific CO2 emission. The optimal lifetime in case where petrol car is replaced by diesel car was analyzed too. [Copyright &y& Elsevier]

Abstract: We establish in this paper the optimization model of group consensus of 2-tuple linguistic preferential relations (LPRGCO Model), put forward three kinds of solutions to this model, and discover in it the convergence of group consensus. To detect the LPRGCO Model, we first build two kinds of optimal matrices as standards to measure the group consensus of 2-tuple linguistic preference relations (LPRs). And to analyze consensus deviations, we then adopt three types of measures, namely, the individual degree of consistency regarding alternative decision pairs, the deviational degree of the group consensus regarding alternative decision pairs, and the degree of group consensus regarding the original 2-tuple LPRs. On the basis of the previous analysis we not only construct an optimization model to probe into the deviation of the group consensus of 2-tuple LPRs by minimizing the weighted arithmetic average of deviation degrees of individual consistency, but also point out three feasible solutions to this optimization model: the optimal solution, satisfactory solutions, and non-inferior solutions. Accordingly, we discover different conditions in terms of the three solutions. And hence, we can from the aforementioned discussion draw a conclusion that the deviation of group consensus either decreases or stays invariant as the number of decision makers (DM) increases. To expatiate on the practical value of the model proposed, we will display in this paper numerical examples. [Copyright &y& Elsevier]

Abstract: Design, implementation and operation of solar thermal electricity plants are no more an academic task, rather they have become a necessity. In this paper, we work with power industries to formulate a multi-objective optimization model and attempt to solve the resulting problem using classical as well as evolutionary optimization techniques. On a set of four objectives having complex trade-offs, our proposed procedure first finds a set of trade-off solutions showing the entire range of optimal solutions. Thereafter, the evolutionary optimization procedure is combined with a multiple criterion decision making (MCDM) approach to focus on preferred regions of the trade-off frontier. Obtained solutions are compared with a classical generating method. Eventually, a decision-maker is involved in the process and a single preferred solution is obtained in a systematic manner. Starting with generating a wide spectrum of trade-off solutions to have a global understanding of feasible solutions, then concentrating on specific preferred regions for having a more detailed understanding of preferred solutions, and then zeroing on a single preferred solution with the help of a decision-maker demonstrates the use of multi-objective optimization and decision making methodologies in practice. As a by-product, useful properties among decision variables that are common to the obtained solutions are gathered as vital knowledge for the problem. The procedures used in this paper are ready to be used to other similar real-world problem solving tasks. [Copyright &y& Elsevier]

Abstract: This paper uses Diffuser Augmented Wind Turbine for reference. According to the characteristics of ocean current movement, this paper gives several dome model programs for the straight blade vertical-axis tidal turbine. Make use of it to increase its output power. This paper gives several dome model programs for the straight blade vertical-axis tidal turbine. And optimum scheme is chosen by numerical simulation. [Copyright &y& Elsevier]

Abstract: In this paper, a weighted combination of different demand vs. price functions referred to as Composite Demand Function (CDF) is introduced in order to represent the demand model of consuming sectors which comprise different clusters of customers with divergent load profiles and energy use habitudes. Derived from the mathematical representations of demand, dynamic price elasticities are proposed to demonstrate the customers’ demand sensitivity with respect to the hourly price. Based on the proposed CDF and dynamic elasticities, a comprehensive demand response (CDR) model is developed in this paper for the purpose of representing customer response to time-based and incentive-based demand response (DR) programs. The above model helps a Retail Energy Provider (REP) agent in an agent-based retail environment to offer day-ahead real time prices to its customers. The most beneficial real time prices are determined through an economically optimized manner represented by REP agent’s learning capability based on the principles of Q-learning method incorporating different aspects of the problem such as price caps and customer response to real time pricing as a time-based demand response program represented by the CDR model. Numerical studies are conducted based on New England day-ahead market’s data to investigate the performance of the proposed model. [Copyright &y& Elsevier]

Plant-wide oscillation detection is an important task in the maintenance of large-scale industrial control systems, owing to the fact that in an interactive multi-loop environment oscillation generated in one loop may propagate to the different parts of the plant. In such a scenario, it is required that different loops oscillating due to a common cause and hence similar frequency may be grouped together. In this paper an adaptive method for plant-wide oscillation detection based on multivariate empirical mode decomposition (MEMD) along with a grouping algorithm is proposed. The method can identify multiple oscillation groups among different variables as well as variables with random noise only. The proposed method is also applicable to both non-linear and non-stationary time series where the techniques based on the conventional Fourier analysis are prone to errors. Within each group that oscillate due to a common cause, the method can also indicate the location of the probable root cause of oscillations. The efficacy of the proposed method is established with the help of both simulation and industrial case studies. [ABSTRACT FROM AUTHOR]

This paper presents an improved scheme for the state-of-health (SOH) estimation, applicable to battery management system (BMS) of electric vehicles. The original scheme requires the prior information for the estimation, which is the prior SOH identified from the last charging. This limit implies that if a battery or its BMS is replaced, the prior SOH stored within the BMS no longer matches with the actual SOH, resulting in a critical error. To avoid this potential but critical pitfall, we newly devise an improved SOH estimation scheme. The original scheme is revised by adopting the fixed-point iteration method into its parameter estimation. By removing dependencies on the prior information, the revised scheme can function regardless of such replacements. The revised scheme is experimentally validated and demonstrated that even without the prior information, it can satisfy the requirement of the SOH estimation (within 3%) thanks to its improved design. [ABSTRACT FROM AUTHOR]

Abstract: Combined cycle power plants have been studied in this paper with the aim of optimizing the heat recovery steam generator using a first and second law approach. To this end, a mathematical model has been developed for determining the optimal steam pressure in a one pressure level heat recovery steam generator, considering that the gas turbine is known. Different objective functions have been analysed in this study, some of which refer only to the exergy balance of the heat recovery steam generator while others involve the whole bottoming cycle. Some constraints for the operating parameters of the power plant have also been taken into account, regarding for instance the steam quality at the turbine outlet and the steam turbine blade height. Some numerical results have been reported in the paper, comparing the different objective functions for heat recovery steam generators coupled with several gas turbines; the developed parametric analysis has been performed in order to evaluate the influence of some parameters on both the heat recovery steam generator and the whole bottoming cycle. [ABSTRACT FROM AUTHOR]

Abstract: Ocean thermal energy is a type of renewable energy. The phase change process of the thermal glider propelled by ocean thermal energy was numerically and experimentally investigated in this paper. The gliding process was analyzed and optimized while the glider was operating in the ocean thermocline near the equator. The results showed that the time of a cycle decreases by 30% and the gliding depth decreases by 40% after optimization. The gliding process was also analyzed when the PCMs were partly melted with the volumetric expansion rate at 50%, 60%, 70%, 80% and 90% of the total value. With the decreasing of the volumetric expansion rate, the depth and the duration of a cycle decrease significantly, but the output work does not decrease obviously. It is helpful to reduce the manufacturing cost and prolong the duration of the glider. In addition, it can improve the energy harvest efficiency from the ocean thermocline. The vehicle''s gliding process can be further investigated in different ocean thermoclines based on the numerical model presented in this paper, which can provide helpful information for optimal design of the thermal glider. [Copyright &y& Elsevier]

Abstract: This paper presents a numerical study on laminar forced convection of water in offset strip-fin microchannels network heat sinks for microelectronic cooling. A 3-dimensional mathematical model, consisting of N–S equations and energy conservation equation, with the conjugate heat transfer between the heat sink base and liquid coolant taken into consideration is solved numerically. The heat transfer and fluid flow characteristics in offset strip-fin microchannels heat sinks are analyzed and the heat transfer enhancement mechanism is discussed. Effects of geometric size of strip-fin on the heat sink performance are investigated. It is found that there is an optimal strip-fin size to minimize the pressure drop or pumping power on the constraint condition of maximum wall temperature, and this optimal size depends on the input heat flux and the maximum wall temperature. The results of this paper are helpful to the design and optimization of offset strip-fin microchannel heat sinks for microelectronic cooling. [Copyright &y& Elsevier]

We present new results where free parameters in spurious oscillations at layers diminishing (SOLD) method are adaptively chosen. Provided numerical results are for conforming piecewise linear finite element space with free parameters from piecewise constant finite element space. We focus on a higher order convergence we discovered in previous paper by Lukáš (2015). [ABSTRACT FROM AUTHOR]

Periodic replacement policies modeled with the history of minimal repairs have been studied extensively. However, in the viewpoint of cost rate, there is no literature to compare replacement polices which are carried out at some periodic times and at a predetermined number of repairs. In this paper, we compare these two types of replacement policies analytically from the optimizations of the integrated models. It will be shown that there always exists a degradation model when any bivariate replacement policy is optimized and this is just the best choice of the comparisons. Not only that, the approaches of whichever occurs first and last are applied to model the above two types of policies, which are named as replacement first and replacement last, respectively, and their comparisons are also made. In addition, we delay the policy at repair to periodic time for easier replacement, and the modified replacement model, which is named as replacement overtime, is compared with the original ones. Numerical examples are also given and agree with all analytical discussions. [ABSTRACT FROM AUTHOR]

An overview of numerical and mathematical modelling-based distributed generation (DG) system optimisation techniques is presented in this review paper. The objective is to compare different aspects of these two broad classes of DG optimisation techniques, explore their applications, and identify potential research directions from reviewed studies. Introductory descriptions of general electrical power system and DG system are first provided, followed by reviews on renewable resource assessment, load demand analysis, model formulation, and optimisation techniques. In renewable resource assessment model review, uncertain solar and wind energy resources are emphasised whereas applications of forecasting models have been highlighted based on their prediction horizons, computational power requirement, and training data intensity. For DG optimisation framework, (solar, wind and tidal) power generator, energy storage and energy balance models are discussed; in optimisation technique section, both numerical and mathematical modelling optimisation methods are reviewed, analysed and criticised with recommendations for their improvements. In overall, this review provides preliminary guidelines, research gaps and recommendations for developing a better and more user-friendly DG energy planning optimisation tool. [ABSTRACT FROM AUTHOR]

Component-based modeling frameworks make it easier for users to access, configure, couple, run and test numerical models. However, they do not typically provide tools for uncertainty quantification or data-based model verification and calibration. To better address these important issues, modeling frameworks should be integrated with existing, general-purpose toolkits for optimization, parameter estimation and uncertainty quantification. This paper identifies and then examines the key issues that must be addressed in order to make a component-based modeling framework interoperable with general-purpose packages for model analysis. As a motivating example, one of these packages, DAKOTA, is applied to a representative but nontrivial surface process problem of comparing two models for the longitudinal elevation profile of a river to observational data. Results from a new mathematical analysis of the resulting nonlinear least squares problem are given and then compared to results from several different optimization algorithms in DAKOTA. [ABSTRACT FROM AUTHOR]

As a set theory-based convex model, the ellipsoidal model provides an attractive framework for treating uncertain-but-bounded variations in the structural reliability analysis and design optimization. However, improper modeling of the uncertainties may give rise to misleading non-probabilistic reliability analysis, thus result in either unsafe or over-conservative designs. This paper presents a systematic study on the mathematical formulation for constructing the minimum-volume ellipsoidal convex model using a given set of sample data, and shows its application in existing methods of non-probabilistic reliability analysis and design optimization of structures with bounded uncertainties. In this method, the uncertain parameters are first divided into groups according to their sources. For each individual group of uncertainties, the minimum-volume ellipsoid problem is reformulated into a semi-definite programming (SDP) problem and thus can be efficiently solved to its global optimum. Further, a linear transformation based on the eigenvalue analysis is employed to map the ellipsoidal model into a standard uncertainty space. This uncertainty modeling technique enables a compact and differentiable bound description of the parameter variations. Moreover, it has another useful property, the affine invariance, which is shown to be necessary for meaningful definition of a non-probabilistic reliability index. The effectiveness and efficiency of the present techniques for convex model construction and the corresponding reliability analysis are demonstrated with numerical examples of structural topology optimization problems with bounded variations arising from different sources. [ABSTRACT FROM AUTHOR]

Let D k , l ( m , n ) be the set of all the integer points in the transportation polytope of k n × l n matrices with row sums lm and column sums km . In this paper we find the sharp lower bound on the tropical determinant over the set D k , l ( m , n ) . This integer piecewise linear programming problem in arbitrary dimension turns out to be equivalent to an integer non-linear (in fact, quadratic) optimization problem in dimension two. We also compute the sharp upper bound on a modification of the tropical determinant, where the maximum over all the transversals in a matrix is replaced with the minimum. [ABSTRACT FROM AUTHOR]

The pilot-control globe valve (PCGV) is a new kind valve with simple structures and low driving energy consumption. It can utilize the pressure difference before and after the valve to control the action of the valve core. However, systematic theoretical research and numerical analysis are deficient at present. In this paper, the mathematical model of PCGV is established and Computational Fluid Dynamics (CFD) method is employed to numerically simulate its dynamic characteristics. Through the analysis of the internal flow field distribution, its working principle is verified. Then three different opening processes with the same spring stiffness are analyzed under different static inlet pressures, and the best design point is obtained by studying the characteristic curves of the valve core’s displacement. The relationship of static inlet pressure and the valve core’s displacement is summarized and the selection formula for the valve design is generalized which can reduce the various design work for further optimization and engineering applications of PCGV. [ABSTRACT FROM AUTHOR]

Abstract: Model updating for the quadratic eigenvalue problem aims to update the model by given eigendata. In this paper, we consider the -weighted model updating problem which can not only preserve the symmetry and definiteness of the original model but also express our confidence in the original model through assigning different confidence weights. We propose an augmented Lagrangian dual method for the -weighted model updating problem. Under some mild assumptions, our method is shown to converge at least linearly. Numerical results illustrate the effectiveness of our method. In addition, we compare our method with the semi-definite programming (SDP) method. Numerical results illustrate that when the scale of the model becomes large our method still works but the SDP method failed to converge. [Copyright &y& Elsevier]

• The original identification model is decomposed into several sub models according to the dimension of output and different forms of parameters. • To solve the unmeasurable noise terms in the information matrices, we construct some auxiliary models based on the obtained parameter estimates. • To cut down the redundant estimates and solve the associate terms , a partially coupled nonlinear parameter optimization algorithm is proposed. A key to the analysis and design of a dynamic system is to establish a suitable mathematical model of the system. This paper investigates the parameter optimization problem of a class of radial basis function-based multivariate hybrid models. Taking into account the high dimensions of the models and different forms of the parameters, the original identification model is separated into several regressive sub-identification models according to the characteristics of model outputs. Some auxiliary models are constructed to solve the unmeasurable noise terms in the information matrices. For the purpose of eliminating the redundant computation and to deal with the associate terms caused by the model decomposition, inspired by the coupling concept, a partially-coupled nonlinear parameter optimization algorithm is proposed for the multivariate hybrid models. Through the computational efficiency analysis and numerical simulation verification, it is shown that the proposed algorithm has low computational complexity and high parameter estimation accuracy. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we give a modified Wei–Yao–Liu conjugate gradient method (Wei et al., 2006 [18]), which will reduce to the original Wei–Yao–Liu method, and possess the sufficient descent property without any line search. Furthermore, we prove that the presented method is globally convergent for nonconvex functions with the weak Wolfe–Powell line search. In a similar way, we also extend these results to the modified Liu–Storey method. Preliminary numerical results show that the proposed methods are effective for the given test problems. [Copyright &y& Elsevier]

Abstract: RFID solutions will improve the traceability of biological samples stored at low temperature (77K) in biobanks. To achieve this goal, the reliability of RFID tags is essential. In this paper, we focus on the reliability aspect of RFID tags in harsh environment and more specifically to assembly design optimization through numerical simulations and accelerated life tests. A package-dimensioned model and a wire-interconnect centered model have been used to assess stress distribution in the package and wire bonds. We also develop a specific versatile test bench to apply thermal cycling while monitoring the functionality of the tags. We investigate three different tag configurations and demonstrate that the main failure mode is related to wire breaks. The occurrence of this failure depends mainly on the nature and thickness of the encapsulant resin which induce compressive and tensile stresses during thermal cycling. FEM results are in good agreement with observed failures. [Copyright &y& Elsevier]

Abstract: Although the grey forecasting model has been successfully employed in many fields and demonstrated promising results, its prediction results may be inaccurate sometimes. For the purposes of enhancing the predictive performance of grey forecasting model and enlarging its suitable ranges, this paper puts forward a novel grey forecasting model termed NGM model and its optimized model, develops a calculative formula for solving the parameters of the novel NGM model through the least squares method, and obtains the time response sequence of NGM model by using differential equation as a procedure for reasoning. It performs a numerical demonstration on the prediction accuracy of NGM model and its optimized models. As shown in the results, the proposed model and it optimized model can enhance the prediction accuracy. Numerical results illustrate that the proposed NGM model and its optimized model are effective. They are suitable for predicting the data sequence with the characteristics of non-homogeneous exponential law. This work makes important contribution to the enrichment of grey prediction theory. [Copyright &y& Elsevier]

Abstract: Cam-modulated linkages that can achieve superior kinematic performance as compared with pure linkages have been widely applied in a variety of automation machinery. The tolerance analysis and synthesis are thus quite essential in the design and manufacture of precision cam-modulated linkages. This paper presents comprehensive and systematic mathematical tools for dealing with the tolerance analysis and synthesis of cam-modulated linkages. Based on the concept of equivalent linkage and the derived correlation between the radial-dimension errors and the normal-direction errors of the cam profile, the sensitivity analysis method for equivalent linkages is introduced for analyzing the tolerances in cam-modulated linkages, whose output error equations can be derived through an analytical means. Then, by incorporating the sensitivity analysis method and the concept of design for manufacturing and assembly (DFMA), an optimization model for synthesizing the tolerances in cam-modulated linkages is developed. The objective of this optimization model is to maximize the manufacturability and assembility of a cam-modulated linkage while maintaining acceptable kinematic accuracy of its output motion. A practical case study of analyzing and synthesizing the tolerances in a cam-modulated linkage type pick-and-place device is then performed to illustrate the presented methods. It shows that the mathematical tools presented can be helpful to the design and manufacture of precision cam-modulated linkages. [Copyright &y& Elsevier]

Abstract: Mathematical optimization methods based on the topological sensitivity analysis have been used to develop innovative ultrasonic imaging methods. With a single illumination of the medium, they have proved experimentally to yield a lateral resolution comparable to classical multiple-illumination techniques. As these methods are based on the numerical simulations of two wave fields, they require extensive computation. A time-domain finite-difference scheme is usually used for that purpose. This paper presents the development of an experimental imaging method based on the topological sensitivity. The numerical cost is reduced by replacing the numerical simulations by simple mathematical operations between the radiation patterns of the array’s transducers and the frequency-domain signals to be emitted. These radiation patterns are preliminary computed once and for all. They were obtained with a finite element model for the anisotropic elastodynamic case and with semi-analytical integrations for the acoustic case. Experimental results are presented for a composite material sample and for a prefractal network immersed in water. A lateral resolution below 2.5 times the wavelength is obtained with a single plane wave illumination. The method is also applied with multiple illuminations, so that objects hidden in complex media can be investigated. [Copyright &y& Elsevier]

Abstract: This study reports on energy efficiency optimization regarding bottom trawls. Efficient fishing gear uses up only a small amount of energy per fish caught. Drag and mouth area during trawling operations affect energy efficiency. Drag causes the energy consumption and the trawl mouth area impacts the quantity of fish caught, hence an energy efficient gear has a low ratio drag on the mouth area. A novel numerical optimization technique using spatial fish distribution is presented in this work. The tool is based on a FEM mechanical model for trawls which consist mostly of netting panels sewn together. This tool is adapted to minimize an objective function namely the drag-to-mouth area ratio. This technique consists in modifying the design of all the panels of the trawl. In this paper the modifications are constant and quantified in terms of mesh number. Moreover the trawl mouth area takes into account the presence of fish within a given depth with respect to sea bottom and the value of the depth is adapted to the fish species of interest. Trawl design optimization with two uniform fish distributions at a given depth (6m and 3m above the sea bed) and one linear distribution at 6m above the sea bed are compared. The application of this tool when designing a bottom trawl for research vessels leads to an energy economy ranging from 16% to 52% under certain assumptions. [Copyright &y& Elsevier]

Abstract: A lithium-ion battery module can comprise a large number of cells, which contain further functional layers and groups. Detailed, mechanistic mathematical modeling of the physicochemical phenomena that occur at different length scales throughout a battery module is therefore a challenging problem. In this paper, we present a method to reduce the computational cost when solving a Li-ion battery model comprising transient equations of change – species, charge, and energy – through model reformulation and a procedure to automate the task of drawing the battery module and solving it numerically. Reformulation is carried out for the model validated with experimental results. The automation not only reduces the overall time to find a numerical solution, but it also removes the chance of human errors during the pre-processing step. The procedure is verified with significant gains in computational cost: the reformulated model is around 40% faster than without the reformulation, and the model for a 50-cell battery module takes only around 14s to set up numerically. The reformulated mathematical model in combination with automated model generation thus opens up avenues for wide-ranging parameter studies, automated multi-objective optimization of design, layout, management strategies and operating conditions of a battery module. [Copyright &y& Elsevier]

Abstract: This paper introduces the numerical model analysis of evolutionary sections (AES) as a tool for the analysis of precast concrete sections constructed in several phases. Constitutive models including both concrete cracking and post-peak response of the materials were implemented. Likewise, the time-dependent behavior of the materials has been considered to model the sequential construction process. In order to validate the results obtained by the model, an experimental campaign (from the literature) was used. The comparison of the experimental results to those numerically obtained was satisfactory. The AES is already in use in several Spanish precast concrete factories for the optimization of bridges constructed with precast – prestressed concrete girders. [Copyright &y& Elsevier]

Abstract: Metamodelling is an increasingly more popular approach for alleviating the computational burden associated with computationally intensive optimization/management problems in environmental and water resources systems. Some studies refer to the metamodelling approach as function approximation, surrogate modelling, response surface methodology or model emulation. A metamodel-enabled optimizer approximates the objective (or constraint) function in a way that eliminates the need to always evaluate this function via a computationally expensive simulation model. There is a sizeable body of literature developing and applying a variety of metamodelling strategies to various environmental and water resources related problems including environmental model calibration, water resources systems analysis and management, and water distribution network design and optimization. Overall, this literature generally implies metamodelling yields enhanced solution efficiency and (almost always) effectiveness of computationally intensive optimization problems. This paper initially develops a comparative assessment framework which presents a clear computational budget dependent definition for the success/failure of the metamodelling strategies, and then critically evaluates metamodelling strategies, through numerical experiments, against other common optimization strategies not involving metamodels. Three different metamodel-enabled optimizers involving radial basis functions, kriging, and neural networks are employed. A robust numerical assessment within different computational budget availability scenarios is conducted over four test functions commonly used in optimization as well as two real-world computationally intensive optimization problems in environmental and water resources systems. Numerical results show that metamodelling is not always an efficient and reliable approach to optimizing computationally intensive problems. For simpler response surfaces, metamodelling can be very efficient and effective. However, in some cases, and in particular for complex response surfaces when computational budget is not very limited, metamodelling can be misleading and a hindrance, and better solutions are achieved with optimizers not involving metamodels. Results also demonstrate that neural networks are not appropriate metamodelling tools for limited computational budgets while metamodels employing kriging and radial basis functions show comparable overall performance when the available computational budget is very limited. [Copyright &y& Elsevier]

Abstract: In this paper, an experimental investigation on diode laser transmission welding of dissimilar thermoplastics between PMMA (polymethyl methacrylate) and ABS (acrylonitrile butadiene styrene) has been carried out. The effect of the laser welding parameters such as laser power, welding speed, stand-off distance and clamp pressure on weld strength and weld width is investigated using response surface methodology (RSM). Planned experiments and subsequent analyses are carried out to develop the mathematical models to establish the correlation between the process parameters and the responses. The adequacy of the developed models is tested using the sequential F-test, lack-of-fit test and the analysis-of-variance (ANOVA) technique. A numerical multi-objective simultaneous optimization technique, in which the RSM is incorporated, is used to find the optimum solutions, according to the desired optimization criteria. In addition to that, a graphical optimization technique is, also implemented which allow identifying a region in the graphic where optimal conditions lay on. [Copyright &y& Elsevier]

Abstract: Many practical control systems can be modeled as switched linear systems with stabilizable and unstabilizable subsystems. In this paper, control synthesis for such a class of systems with actuator saturation is well investigated in the continuous-time and discrete-time cases. Based on the time-dependent switching signals and multiple Lyapunov function method, stabilization conditions are established in terms of LMIs. To obtain an attractive region as large as possible, the optimization problems are formulated. As the applications, the asynchronously switched control and intermittent control under actuator saturation are discussed. Numerical examples and simulations are presented to illustrate the feasibility and values of the proposed results. [Copyright &y& Elsevier]

Abstract: The recent nuclear leakage accidents have made evacuation a leading issue in engineering emergency management. Evacuation routing is one of key problems for helping people move to safety. In this paper, a bi-objective model is proposed to optimize the engineering route assignment, with the possibilities of secondary evacuation in consideration. This model is aimed to minimize the maximum travel time and minimize the secondary evacuation expected costs simultaneously. An approximation algorithm with polynomial complexity is designed to solve this model. Finally, a numerical example is given to demonstrate the actual significance of our model the validity of this algorithm. [Copyright &y& Elsevier]

Abstract: Cross-efficiency evaluation is an extension of Data Envelopment Analysis (DEA) that permits not only the determination of a ranking of Decision Making Units (DMUs) but also the elimination of unrealistic weighting schemes, thereby rescinding the necessity for the inclusion of individual judgements in the models. The main deficiency of the procedure is the non-uniqueness of the optimal weights, which results in the peer evaluations dependences, for instance, on the software used to determine DMU’s efficiencies. This shortfall justifies the inclusion of secondary goals in order to determine cross-efficiency values. In this paper a new proposal of a secondary goal is studied. The idea is related with that proposed in Wu et al. (2009), in which the objective is the optimization of the rank position of the DMU under evaluation. In the procedure proposed here, an incentive to break level-pegging ties between alternatives is introduced by considering that efficiency scores induce a weak order of alternatives. The model is illustrated with a preference-aggregation application. [Copyright &y& Elsevier]

Abstract: The optimization problem addressed in this paper is an advanced form of the flexible job shop scheduling problem (FJSP) which also covers process plan flexibility and separable/non-separable sequence dependent setup times in addition to routing flexibility. Upon transforming the problem into an equivalent network problem, two mixed integer goal programming models are formulated. In the first model (Model A) the sequence dependent setup times are non-separable. In the second one (Model B) they are separable. Model B is obtained from Model A with a minor modification. The formulation of the models is described on a small sized numerical example and the solutions are interpreted. Finally, computational results are obtained on test problems. [Copyright &y& Elsevier]

Abstract: This paper investigates maintenance policy and length of extended warranty for repairable products from the seller’s viewpoint. When the product failed within the base and extended warranty periods, product failures are rectified using minimal repair. To reduce the number of product failures, the seller performs imperfect preventive maintenance (PM) actions when the age of the product reaches a controlled-limit within the base and extended warranty periods. After the base warranty period expires, the seller gives a discount of purchasing extended warranty expense if the consumer purchases the extended warranty for products. Under this maintenance scheme, the mathematical model of profit is constructed and then the optimal controlled-limit, the number and degree of PM and the length of extended warranty are obtained such that the expected total profit is maximized for the seller. Finally, numerical examples are given to illustrate the influences of the optimal length of the extended warranty and the maintenance policy for profit model. [Copyright &y& Elsevier]

Abstract: Most of the advanced integrated energy systems need a heat recovery steam cycle (HRSC), either fired or unfired, that recovers the waste heat from gas turbines and process units in order to generate electric power and supply mechanical power to compressors, heat to endothermic processes, and steam to external users. The key feature of such HRSCs is the integration between the heat recovery steam generator (HRSG) and the external heat exchangers. This paper presents a rigorous mathematical programming model, a linear approximation, and a two-stage algorithm for optimizing the design of integrated HRSGs and HRSCs, simultaneously considering the HRSG together with the heat recovery steam network and the intensive steam cycle variables. A detailed application of the methodology is described for an integrated gasification combined cycle plant with CO2 capture and results for other interesting plants are reported. A significant efficiency gain is obtained with respect to usual practice designs. [Copyright &y& Elsevier]

Abstract: This paper presents a continuous facility location model with fuzzy methodology. The developments concern mainly to some drawbacks in the initial model which takes it far from being used in practice. A fuzzy modeling method is proposed to estimate the required functions in the initial model. Structure identification in the proposed fuzzy modeling method is carried out using subtractive clustering, and parameter identification is conducted via some heuristics as well as an optimization problem. Furthermore, a simulation method along with some heuristic relations is used for implementation and evaluation of the modified model. Efficiency of the proposed method to fuzzy modeling as well as the proposed simulation method is presented by a numerical example. [Copyright &y& Elsevier]

Abstract: Spare parts and maintenance are closely related logistics activities where maintenance generates the need for spare parts. When preventive maintenance is present, it may need more spare parts at one time because of the planned preventive maintenance activities. This paper considers the joint optimisation of three decision variables, e.g., the ordering quantity, ordering interval and inspection interval. The model is constructed using the well-known Delay-Time concept where the failure process is divided into a two-stage process. The objective function is the long run expected cost per unit time in terms of the three decision variables to be optimised. Here we use a block-based inspection policy where all components are inspected at the same time regardless of the ages of the components. This creates a situation that the time to failure since the immediate previous inspection is random and has to be modelled by a distribution. This time is called the forward time and a limiting but closed form of such distribution is obtained. We develop an algorithm for the optimal solution of the decision process using a combination of analytical and enumeration approaches. The model is demonstrated by a numerical example. [Copyright &y& Elsevier]

Abstract: In this paper, we make a modification to the Liu–Storey (LS) conjugate gradient method and propose a descent LS method. The method can generate sufficient descent directions for the objective function. This property is independent of the line search used. We prove that the modified LS method is globally convergent with the strong Wolfe line search. The numerical results show that the proposed descent LS method is efficient for the unconstrained problems in the CUTEr library. [Copyright &y& Elsevier]

Abstract: It is critical to understand and manage the thermal effects in optimizing the performance and durability of proton exchange membrane fuel cell (PEMFC) stack. And building up the control-oriented thermal model of PEMFC stack is necessary. The thermal model, a set of differential equations, is established according to the conservation equations of mass and energy, which can be used to reflect truly the actual temperature response of PEMFC stack, however, the expressions of the model are too complicated to be used in the design of control. For this reason, the expressions are converted into the affine state space control-oriented model in detail for the variable structure control (VSC) strategy. Meanwhile, the accurate model must be established for the VSC and the parameters of VSC laws should be optimized. Consequently, a novel genetic algorithm (NGA) is developed to optimize the parameter of thermal-model-oriented control law for PEMFC stack. Finally, numerical test results demonstrate the effectiveness and rationality of the method proposed in this paper. It lays the foundation for the realization of online thermal management of PEMFC stack based on VSC. [Copyright &y& Elsevier]

Abstract: Expensive optimization aims to find the global minimum of a given function within a very limited number of function evaluations. It has drawn much attention in recent years. The present expensive optimization algorithms focus their attention on metamodeling techniques, and call existing global optimization algorithms as subroutines. So it is difficult for them to keep a good balance between model approximation and global search due to their two-part property. To overcome this difficulty, we try to embed a metamodel mechanism into an efficient evolutionary algorithm, low dimensional simplex evolution (LDSE), in this paper. The proposed algorithm is referred to as the low dimensional simplex evolution extension (LDSEE). It is inherently parallel and self-contained. This renders it very easy to use. Numerical results show that our proposed algorithm is a competitive alternative for expensive optimization problems. [Copyright &y& Elsevier]

Abstract: Data assimilation obtains improved estimates of the state of a physical system by combining imperfect model results with sparse and noisy observations of reality. In the four dimensional variational (4D-Var) framework data assimilation is formulated as an optimization problem, which is solved using gradient based optimization methods. The 4D-Var gradient is obtained by forcing the adjoint model with observation increments. The construction of the adjoint model requires considerable development effort. In the continuous approach the adjoint differential equations are discretized. In the discrete approach the numerical solution of the forward equations is differentiated. The two routes lead to different gradients. In this paper we investigate numerically the effect of using discrete and continuous adjoints of the advection equation in chemical transport modeling. Continuous advection adjoints are easily implemented by calling the same advection subroutines as the forward model, with a sign change for the winds, and with rescaling the solution. Discrete advection adjoints involve the differentiation of a nonlinear, monotonic advection scheme like the piecewise parabolic method. The numerical experiments are carried out with CMAQ-ADJ. The results show that, while discrete advection adjoints are more accurate in point-to-point comparisons against finite differences, the continuous adjoints of advection perform better as gradients for optimization in 4D-Var data assimilation. [Copyright &y& Elsevier]

Abstract: The multiple attribute group decision making (MAGDM) problem with intuitionistic fuzzy information investigated in this paper is very useful for solving complicated decision problems under uncertain circumstances. Since experts have their own characteristics, they are familiar with some of the attributes, but not others, the weights of the decision makers to different attributes should be different. We derive the weights of the decision makers by aggregating the individual intuitionistic fuzzy decision matrices into a collective intuitionistic fuzzy decision matrix. The expert has a big weight if his evaluation value is close to the mean value and has a small weight if his evaluation value is far from the mean value. For the incomplete attribute weight information, we establish some optimization models to determine the attribute weights. Furthermore, we develop several algorithms for ranking alternatives under different situations, and then extend the developed models and algorithms to the MAGDM problem with interval-valued intuitionistic fuzzy information. Numerical results finally illustrate the practicality and efficiency of our new algorithms. [Copyright &y& Elsevier]

Abstract: In this paper, single and bi-layered tube hydroforming processes were numerically simulated using the finite element method. It was found that the final bulges heights resulted from the models were in good agreement with the experimental results. Both types of modeling have been kept with the same geometry, tube material, and process parameters to compare between the obtained hydroformed products (branch height, thickness reduction, and wrinkling) using different loading path types. Results were discussed. [Copyright &y& Elsevier]

Abstract: In today’s competitive markets, effective product portfolio is critical for manufacturers that offer several products. From manufacturers’ perspective, the diversity must be maintained in a level in which the engineering costs do not exceed the acquired advantages of increased market share. On the other hand, product portfolio diversity is prominent for customers. In addition, manufacturers should always be careful about competitors activity. Therefore, we consider the problem of product portfolio management (PPM) in a competitive environment. This paper constructs a game theory-based mathematical model to deal with this new PPM problem. In this presented mathematical model, the PPM problem is formulated as a 2-person non-cooperative game with complete information. Each player has a set of strategies which correspond to the feasible product portfolios. Every payoff is determined by the procedure that considers the customer–engineering interaction in product portfolio planning, which aims to optimize product portfolio for a target market segment, and proposed a maximizing surplus share model for it. Therefore, obtaining the optimal product portfolio is determined by the Nash equilibrium point of this game. Finally, a numerical example is presented to demonstrate the feasibility of the approach. [Copyright &y& Elsevier]

Abstract: This paper develops two component-level control-limit preventive maintenance (PM) policies for systems subject to the joint effect of partial recovery PM acts (imperfect PM acts) and variable operational conditions, and investigates the properties of the proposed policies. The extended proportional hazards model (EPHM) is used to model the system failure likelihood influenced by both factors. Several numerical experiments are conducted for policy property analysis, using real lifetime and operational condition data and typical characterization of imperfect PM acts and maintenance durations. The experimental results demonstrate the necessity of considering both factors when they do exist, characterize the joint effect of the two factors on the performance of an optimized PM policy, and explore the influence of the loading sequence of time-varying operational conditions on the performance of an optimized PM policy. The proposed policies extend the applicability of PM optimization techniques. [Copyright &y& Elsevier]

Abstract: In this paper, an interactive segmentation method is proposed, which is based on an improved Chan–Vese model, i.e. multiple piecewise constant model with geodesic active contour. The k-means method is used to learn the models of the foreground and background, which are the optimal piecewise constant approximation of the original image according to the input seeds clue by the user. Based on the piecewise constant models of the foreground and background, the multiple piecewise constant with a geodesic active contour energy function can be minimized by effective graph cuts algorithm, and the minimum cuts can be used to partition the image into the foreground and background. Numerical experiments demonstrate the superior performance of the proposed interactive foreground extraction method based on the improved Chan–Vese model compared to the original Chan–Vese model by simple user interaction. [Copyright &y& Elsevier]

Abstract: Total variation minimisation is a well-established method for digital image restoration. Its implicit preservation of edges permits the derivation of anisotropic models for a qualitative improvement at corners. This paper is a synopsis of anisotropic models with state-of-the-art insights into the numerics of isotropic models. We generalise two representative models from both branches of research. This formulation leads to a general convergent algorithm and a general highly efficient algorithm which apply for both cases. A transfer of the discretisation from the anisotropic model to the isotropic setting results in an improvement of rotational invariance. [ABSTRACT FROM AUTHOR]