A min—sum—max resource allocation problem

In this paper we describe a class of resource allocation problems with a min-sum-max objective function. We first discuss practical applications of the problem. We then present a result on the computational complexity of the problem. We propose an implicit enumeration procedure for solving the general case of the problem, and report on our computational experience with the solution procedure.     

How to park freight trains on rail–rail transshipment yards: the train location problem

In modern rail–rail transshipment yards huge gantry cranes spanning all railway tracks allow for an efficient transshipment of containers between different freight trains. This way, multiple trains loaded with cargo for varying destinations can be consolidated to a reduced number of homogeneous trains, which is an essential requirement of hub-and-spoke railway systems. An important problem during the daily operations of such a transshipment yard is the train location problem, which assigns each train of a given pulse to a railway track (vertical position) and decides on each train’s parking position on the track (horizontal position), so that the distances of container movements are minimized and the overall workload is equally shared among cranes. For this problem a mathematical model is presented; different heuristic solution procedures are described and tested in a comprehensive computational study. The results show that our procedures allow for a remarkable reduction of train processing time compared with typical real-world train location policies.     

A hybrid SVM and supervised learning approach to fuzzy min‐max hyperbox classifiers

Abstract

In this paper, a fuzzy min‐max hyperbox classifier is designed to solve M‐class classification problems using a hybrid SVM and supervised learning approach. In order to solve a classification problem, a set of training patterns is gathered from a considered classification problem. However, the training set may include several noisy patterns. In order to delete the noisy patterns from the training set, the support vector machine is applied to find the noisy patterns so that the remaining training patterns can describe the behavior of the considered classification system well. Subsequently, a supervised learning method is proposed to generate fuzzy min‐max hyperboxes for the remaining training patterns so that the generated fuzzy min‐max hyperbox classifier has good generalization performance. Finally, the Iris data set is considered to demonstrate the good performance of the proposed approach for solving this classification problem.     

A meshless method using the Takagi–Sugeno fuzzy model

This article proposes a new strong-form meshless method using the Takagi–Sugeno fuzzy model (MTSF) for solving differential equations (DEs). Considering the conventional fuzzy model, the fuzzy inference system (FIS) can be categorized into two architectures, a simple rule base using the Euclidean distance in a multidimensional space (Simple-FIS), and an adaptive neuro-fuzzy inference system (ANFIS). Accordingly, MTSF also can be implemented using Simple-FIS and ANFIS. Based on the two architectures, an approximation scheme for continuous functions is drawn out first. In turn, the derivation is further proposed in which the differential functions are approximated using two independent sets of points, one for the collocation point and the other for the rule point. Solving higher-order DEs becomes possible by following the derivations, and eventually numerical solutions can be obtained. Several examples of one-dimensional ordinary and two-dimensional partial DEs (ODEs and PDEs) are presented to demonstrate the performance of the MTSF method. By MTSF, solutions solved using Simple-FIS and using ANFIS are compared. Variations in boundary conditions and membership function parameters are also studied to examine the agreement among numerical solutions.     

A phase-field model for electrode reactions with Butler–Volmer kinetics

A novel phase-field model for electrochemical processes is formulated, in which the Butler–Volmer kinetics at the electrode/electrolyte interface is taken into account. Using the model, the kinetics and morphology of the electrode/electrolyte interface during an electrode reaction have been investigated. The numerical result satisfies the Nernst equation and Gibbs–Thomson effect at planar and curved interfaces in the equilibrium system, respectively. In addition, the Butler–Volmer relation between the growth velocity of the electrode/electrolyte interface and the overpotential during the electrode reaction is confirmed. Moreover, the morphology of the electrode/electrolyte interface is examined as a function of the applied voltage and reaction coefficient. The tip radius of the electrodeposit is proportional to the inverse of the square root of the growth velocity, which agrees with the dendrite growth theory for the solidification process.     

Macroscopic model with anisotropy based on micro–macro information

Physical experiments can characterize the elastic response of granular materials in terms of macroscopic state variables, namely volume (packing) fraction and stress, while the microstructure is not accessible and thus neglected. Here, by means of numerical simulations, we analyze dense, frictionless granular assemblies with the final goal to relate the elastic moduli to the fabric state, i.e., to microstructural averaged contact network features as contact number density and anisotropy. The particle samples are first isotropically compressed and then quasi-statically sheared under constant volume (undrained conditions). From various static, relaxed configurations at different shear strains, infinitesimal strain steps are applied to “measure” the effective elastic response; we quantify the strain needed so that no contact and structure rearrangements, i.e. plasticity, happen. Because of the anisotropy induced by shear, volumetric and deviatoric stresses and strains are cross-coupled via a single anisotropy modulus, which is proportional to the product of deviatoric fabric and bulk modulus (i.e., the isotropic fabric). Interestingly, the shear modulus of the material depends also on the actual deviatoric stress state, along with the contact configuration anisotropy. Finally, a constitutive model based on incremental evolution equations for stress and fabric is introduced. By using the previously measured dependence of the stiffness tensor (elastic moduli) on the microstructure, the theory is able to predict with good agreement the evolution of pressure, shear stress and deviatoric fabric (anisotropy) for an independent undrained cyclic shear test, including the response to reversal of strain.     

A fuzzy AHP evaluation model for buyer–supplier relationships with the consideration of benefits,opportunities, costs and risks

With increasingly fierce global competition, firms in various industries need to build a cooperative buyer–supplier relationship to survive and to acquire reasonable profit. Even though the literature on various types of collaboration between firms is abundant and the works on supplier selection models are numerous, the research that provides a mathematical model for the selection of the most appropriate form of buyer–supplier relationship is very limited. Existing buyer–supplier evaluation models usually only consider the benefits from the relationship, but not the opportunities, costs and risks that may need to be confronted. The main objective of this study is to propose an analytical approach to evaluate the forms of buyer–supplier relationship between a manufacturer and its supplier. A fuzzy analytic hierarchy process (AHP) model, which applies fuzzy set theory and the benefits, opportunities, costs and risks (BOCR) concept, is constructed to deal with uncertainty and to consider various aspects of alternatives. Multiple factors that affect the success of the relationship are analysed by incorporating experts’ opinions on their priority of importance, and a performance ranking of the buyer–supplier forms is obtained. A case study of selecting the most appropriate buyer–supplier form between a TFT-LCD manufacturer and its colour filter supplier is presented, and the proposed model is applied to facilitate the decision process. The proposed model is a general form that can be tailored and applied by firms that are making decisions on buyer–supplier relationship.     

A nonlinear viscoelastic–viscoplastic model for adhesives

We consider the nonlinear viscoelastic–viscoplastic behavior of adhesives. We develop a one-dimensional nonlinear model by combining Schapery’s nonlinear single integral model and Perzyna’s viscoplastic model. The viscoplastic strain was solved iteratively using the von Mises yield criterion and nonlinear kinematic hardening. The combined viscoelastic–viscoplastic model was solved using Newton’s iteration and implemented into a finite element model. The model was calibrated using creep-recovery data from bulk adhesives and verified from the cyclic behavior of the bulk adhesives. The finite element model results agreed with experimental creep and cyclic responses, including recoverable and permanent strain after load removal. Although the contribution of the viscoplastic strain was small, both viscoplastic and viscoelastic components of strain response were required to describe the adhesive creep and cyclic response.

     

A particle packing model for sand–silt mixtures with the effect of dual-skeleton

The study of particle packing models for binary mixtures is important in the field of granular materials, from both theoretical and practical perspectives. A number of particle packing models have been developed for predicting packing density (or void ratio) of a binary mixture. However, the measured results and the predicted values do not always agree with each other, particularly in the range of fines content between 25 and 50%. It is postulated herein that the discrepancies between the measured results and the predicted values are primarily due to the incorrect assumptions used in the existing models. In the existing models, the packing density is determined from one of the following two assumed mechanisms of particle mixing: (1) the mixed packing has a dominant large-particle skeleton and the small particles fill the voids of the large-particle skeleton, or (2) the mixed packing has a dominant small-particle skeleton and the large particles are embedded in the small-particle skeleton. It is obvious that the first assumed mechanism is only applicable for mixtures with low fines content, whereas the second assumed mechanism is only applicable to mixtures with high fines content. Therefore, the predictions from existing models are unsuitable for mixtures with medium fines content, such as a mixture of fines content between 25 and 50%. In this study, a 3-D discrete element simulation is carried out to show that, for a mixture of medium fines content, the packing structure has a dual-skeleton, which is neither dominated by a large nor small-particle skeleton. Then, we postulate that, in the mixed packing, both mechanisms can take place: filling of small particles and embedment of large particles. The concepts of “dual-skeleton index” and “index size” are proposed to account for the interactive effects of filling and embedment. Based on this postulation, we develop an analytical method, which has the capability of predicting minimum void ratio for sand–silt mixtures with various fines contents. The developed model is then validated by the experimental results obtained from 16 types of sand–silt mixtures.     

An integrated CPU–GPU heuristic inspired on variable neighbourhood search for the single vehicle routing problem with deliveries and selective pickups

Environmental issues have become increasingly important to industry and business in recent days. This trend forces the companies to take responsibility for product recovery, and proper recycling and disposal, moving towards the design of sustainable green supply chains. This paper addresses the backward stream in transportation of products, by means of reverse logistics applied to vehicle routing. This problem, called single vehicle routing problem with deliveries and selective pickups, consists in finding a route that starts from the depot and visits all delivery customers. Some pickup customers may also be visited, since the capacity of the truck is not exceeded, and there is also a revenue associated with each pickup. We develop an algorithm inspired on the variable neighbourhood search metaheuristic that explores the power of modern graphics processing unit (GPU) to provide routes in reasonable computational time. The proposed algorithm called four-neighbourhood variable neighbourhood search (FN-VNS) includes a novel high-quality initial solution generator, a CPU–GPU integrated perturbation strategy and four different neighbourhood searches implemented purely in GPU for the local search phase. Our experimental results show that FN-VNS is able to improve the quality of the solution for 51 instances out of 68 instances taken from the literature. Finally, we obtained speedups up to 14.49 times, varying from 17.42 up to 76.84 for each local search, measured over a set of new large-size instances.     

A new scheduling technique for the resource–constrained project scheduling problem with discounted cash flows

In this paper, we discuss the resource–constrained project scheduling problem with discounted cash flows. We introduce a new schedule construction technique which moves sets of activities to improve the project net present value and consists of two steps. In particular, the inclusion of individual activities into sets, which are then moved together, is crucial in both steps. The first step groups the activities based on the predecessors and successors in the project network, and adds these activities to a set based on their finish time and cash flow. The second step on the contrary does so based on the neighbouring activities in the schedule, which may but need not include precedence related activities. The proposed scheduling method is implemented in a genetic algorithm metaheuristic and we employ a penalty function to improve the algorithm’s feasibility with respect to a tight deadline. All steps of the proposed solution methodology are tested in detail and an extensive computational experiment shows that our results are competitive with existing work.     

A label‐based information flow control model for object‐oriented systems

Abstract

This paper proposes a label‐based information flow control model to prevent information leakage within object‐oriented systems. It offers the features of: (a) adapting to dynamic object state change, (b) adapting to dynamic role change, (c) preventing indirect information leakage, (d) detailing the control granularity to variables, (e) allowing purpose‐oriented method invocation, (f) controlling method invocation through argument sensitivity, (g) allowing declassification, and (h) allowing only trusted sources to write a variable.     

Cost–volume–profit analysis under uncertainty: a model with fuzzy estimators based on confidence intervals

In this paper we express the uncertainty existing in cost–volume–profit analysis via a new method that constructs fuzzy estimators for the parameters of a given probability distribution function using statistical data. First we present a fuzzy function for the cost and we search for the optimal solution among alternatives as Finch and Gavirneni [2006, International Journal of Production Research, 44 (20), 4329–4342] do, but here we use fuzzy estimators for the variable costs. As a consequence, we formulate a fuzzy number that represents the difference between the costs of the alternatives. Furthermore, we consider conditions of ‘complete’ uncertainty when a company needs to choose between two products and we express the profits and the risk via fuzzy estimators. Finally, under the same conditions of uncertainty we express the breakeven point when the income equals the total cost.     

A Dirichlet–Neumann cost functional approach for the Bernoulli problem

The Bernoulli problem is rephrased into a shape optimization problem. In particular, the cost function, which turns out to be a constitutive law gap functional, is borrowed from inverse problem formulations. The shape derivative of the cost functional is explicitly determined. The gradient information is combined with the level set method in a steepest descent algorithm to solve the shape optimization problem. The efficiency of this approach is illustrated by numerical results for both interior and exterior Bernoulli problems.     

Improved robust exponential stability for Takagi–Sugeno fuzzy uncertain systems with time-varying delays

This paper concerns managing the robust exponential stability problem of uncertain Takagi–Sugeno fuzzy systems with time-varying delay by employing a further improved integral inequality matrix approach. Based on the linear matrix inequality (LMI) approach, delay-dependent robust exponential stability criteria have been developed. By taking the relationship among the time-varying delay, its upper bound and their difference into account, some less conservative LMI-based delay-dependent robust exponential stability criteria are obtained without ignoring any useful terms in the derivative of Lyapunov–Krasovskii functionals. Maximum allowable upper bound for time-varying delays is determined. Numerical examples are provided to show that the obtained results significantly improve the allowed upper bounds of delay size over some methods existing in the literature.     

A nonlinear viscoelastic–viscoplastic constitutive model for adhesives under creep

Mechanics of Time-Dependent Materials - In this study, we consider the nonlinear viscoelastic–viscoplastic behavior of adhesive films in scarf joints. We develop a three-dimensional nonlinear...     

A model for the prediction of liquid–liquid interfacial energies

A model for the calculation of liquid–liquid interfacial energies is presented. It is based on the assumption that the interface can be treated as a separate thermodynamic phase. Its derivation has been performed in an analogous way as the derivation of the Butler equation for the surface tension of liquid alloys. It requires as input parameters the excess free energy and the compositions of the bulk phases as functions of temperature. In addition, it also requires the partial molar volumes of the components. Comparison with existing experimental data for Al–Pb, Al–In, and Cu–Co in a non-equilibrium state shows very good agreements. For Al–Bi, the experimental data are either over or underestimated by a factor of ≈1.7, depending on which of the two thermodynamic assessments is used. For the Al-based systems, the calculated Al-mole fraction in the interface layer is close to the arithmetic average of the Al-mole fractions of the bulk phases.     

A simple model for a minimal environment: the two-atom Tavis–Cummings model revisited

Individual quantum systems may be interacting with surrounding environments having a small number of degrees of freedom. Here we discuss a simple toy model: a system constituted by a two-level atom (atom 1) interacting with a single mode cavity field which is (weakly) coupled to a small environment (atom 2). We investigate the influence of the minimal environment on the dynamics of the linear entropy and the atomic dipole squeezing of atom 1, as well as the entanglement between atom 1 and the field. We also obtain the full analytical solution of the two-atom Tavis–Cummings model for both arbitrary coupling strengths and frequency detunings, necessary to analyse the influence of the field-environment detuning on the evolution of the system’s quantum properties. For complementarity, we discuss the role of the degree of mixedness of the environment by analysing the time-averaged linear entropy of atom 1.