This paper develops a so-called pantographing self adative gap element type contact strategy. Due to the manner of formulation, the scheme has the capability to handle; large deformations in the contact zone; contact initiation in structure exhibiting either positive or indefinite stiffness characteristics; kinematic and material nonlinearity as well as; self adaptively adjusts load/time stepping. In this context, contact in pre and postbuckling structure can be treated. To illustrate the scheme, several benchmark problems are presented. These include contacting structure involving large deformation kinematics, inelastic behavior as well as pre and postbuckling stiffness characteristics. 相似文献
A variety of buyer coalition schemes already exist in the current e-Commerce literature by which buyers form some sort of coalition in order to enjoy added discounts as a result of purchasing in larger bundles. One major problem in all existing schemes is that none of those schemes explicitly treat the coalition process as a collaborative business process; and as a result, the awareness and knowledge-sharing requirements are not explicitly recognized in the design process of the existing systems. This study proposes a conceptual framework for a buyer coalition system called the Awareness-based Buyer Coalition (ABC) system that allows a buyer to bid on the basis of various levels of awareness that s/he may have about other roles’ actions/intentions. The study is an early attempt for explicitly considering awareness and knowledge-sharing requirements of various roles within the buyer coalition process. The theoretical foundations of the study are rooted in the fields of Game Theory, e-Commerce, and Knowledge Management. The research methodology adopted for the study is design science. Various existing buyer coalition algorithms were reviewed and their strengths and weaknesses identified in terms of addressing the information-sharing needs of collaborating buyers. Furthermore, the existing literature on Knowledge Management was reviewed in order to identify an appropriate process model for the proposed buyer coalition framework with specific emphasis on awareness and knowledge-sharing requirements of its collaborating actors. For validation of the proposed conceptual model simulation software was developed to demonstrate results of a variety of simulations for the proof of the concept. 相似文献
The metaheuristic optimization algorithms are relatively new optimization algorithms introduced to solve optimization problems in recent years. For example, the firefly algorithm (FA) is one of the metaheuristic algorithms inspired by the fireflies' flashing behavior. However, its weakness in terms of exploration and early convergence has been pointed out. In this paper, two approaches were proposed to improve the FA. In the first proposed approach, a new improved opposition-based learning FA (IOFA) method was presented to accelerate the convergence and improve the FA's exploration capability. In the second proposed approach, a symbiotic organisms search (SOS) algorithm improved the exploration and exploitation of the first approach; two new parameters set these two goals, and the second approach was named IOFASOS. The purpose of the second method is that in the process of the SOS algorithm, the whole population is effective in the IOFA method to find solutions in the early stages of implementation, and with each iteration, fewer solutions are affected in the population. The experiments on 24 standard benchmark functions were conducted, and the first proposed approach showed a better performance in the small and medium dimensions and exhibited a relatively moderate performance in the higher dimensions. In contrast, the second proposed approach was better in increasing dimensions. In general, the empirical results showed that the two new approaches outperform other algorithms in most mathematical benchmarking functions. Thus, The IOFASOS model has more efficient solutions.
Making optimal use of available resources has always been of interest to humankind, and different approaches have been used in an attempt to make maximum use of existing resources. Limitations of capital, manpower, energy, etc., have led managers to seek ways for optimally using such resources. In fact, being informed of the performance of the units under the supervision of a manager is the most important task with regard to making sensible decisions for managing them. Data envelopment analysis (DEA) suggests an appropriate method for evaluating the efficiency of homogeneous units with multiple inputs and multiple outputs. DEA models classify decision making units (DMUs) into efficient and inefficient ones. However, in most cases, managers and researchers are interested in ranking the units and selecting the best DMU. Various scientific models have been proposed by researchers for ranking DMUs. Each of these models has some weakness(es), which makes it difficult to select the appropriate ranking model. This paper presents a method for ranking efficient DMUs by the voting analytic hierarchy process (VAHP). The paper reviews some ranking models in DEA and discusses their strengths and weaknesses. Then, we provide the method for ranking efficient DMUs by VAHP. Finally we give an example to illustrate our approach and then the new method is employed to rank efficient units in a real world problem. 相似文献
Microsystem Technologies - In the recent past, multiphase power generation, power transmission, and multiphase drive system are the main focus of research due to their several advantages over... 相似文献
Conventional sliding mode control (SMC) has been extensively applied in controlling spacecrafts because of its appealing characteristics such as robustness and a simple design procedure. Several methods such as second-order sliding modes and discontinuous controllers are applied for the SMC implementation. However, the main problems of these methods are convergence and error tracking in a finite amount of time. This paper combines an improved dynamic sliding mode controller and model predictive controller for spacecrafts to solve the chattering phenomenon in traditional sliding mode control. To this aim, this paper develops dynamic sliding mode control for spacecraft’s applications to omit the chattering issue. The proposed approach shows robust attitude tracking by a set of reaction wheels and stabilizes the spacecraft subject to disturbances and uncertainties. The proposed method improves the performance of the SMC for spacecraft by avoiding chattering. A set of simulation results are provided that show the advantages and improvements of this approach (in some sense) compared to SMC approaches. 相似文献
Artificial Life and Robotics - This paper describes the design and performance evaluation of a flexible wearable haptic device that aims to realize full kinesthetic haptic feedback for application... 相似文献
Distributed fractional derivative operators can be used for modeling of complex multiscaling anomalous transport, where derivative orders are distributed over a range of values rather than being just a fixed integer number. In this paper, we consider the space-time Petrov–Galerkin spectral method for a two-dimensional distributed-order time-fractional fourth-order partial differential equation. By applying a proper Gauss-quadrature rule to discretize the distributed integral operator, the problem is converted to a multi-term time-fractional equation. Then, the proposed method for solving the obtained equation is based on using Jacobi polyfractonomial, which are eigenfunctions of the first kind fractional Sturm–Liouville problem (FSLP), as temporal basis and Legendre polynomials for the spatial discretization. The eigenfunctions of the second kind FSLP are used as temporal basis in test space. This approach leads to finding the numerical solution of the problem through solving a system of linear algebraic equations. Finally, we provide some examples with smooth solutions and finite regular solutions to numerically demonstrate the efficiency, accuracy, and exponential convergence of the proposed method.
Proper planning of preventive maintenance (PM) is crucial in many industries such as oil transmission pipelines, automotive and food industries. A critical decision in the PM plans is to determine frequencies and types of maintenance actions in order to achieve a certain level of system availability with a minimum total cost. In this paper, we consider the problem of obtaining availability-based non-periodic optimal PM planning for systems with deteriorating components. The objective is to sustain a certain level of availability with the minimal total maintenance-related costs. In the proposed approach, the planning horizon is divided into some inspection periods of equal intervals. For any given interval, a decision must be made to perform one of the three actions on each component; inspection, preventive repair and preventive replacement. Any of these activities has different effects on the reliability of the components and the corresponding distinct costs based on the required recourses. The cost function includes the cost for repair, replacement, system downtime and random failures. System availability and PM resources are the main constraints considered. Since the proposed model is combinatorial in nature involving non-linear decision variables, a simulated annealing algorithm is employed to provide good solutions within a reasonable time. 相似文献
