关键词： Multi-pair contact   Contact pressure   Localized tooth contact   Spiral bevel gear   Transmission error function  

摘要： The problem of contact pressure evaluation in gears with predesigned parabolic function of transmission errors and with localized contact is considered. It is proposed that several tooth pairs are in contact simultaneously. We construct an algorithm to define the torque transmitted by each pair in contact. Number of pairs in simultaneous contact depends on applied load and phase of meshing. This number is not known in advance. The feature of the algorithm is an automatic detection of the tooth pair number that is in contact in any phase of meshing under load. The algorithm allows you to define forces and torques that are transmitted on each of the pairs of teeth being in contact. Moreover, it allows determining the contact pressure and tooth-to-tooth accuracy of transmission. The proposed algorithm is universal and can be used to study the multi-pair contact in any gears. An application of the algorithm for a spiral bevel gear has been demonstrated. It is shown that tooth overlap factor, dimensions of instant contact patch, tooth bearing contact and tooth-to-tooth accuracy of gears increase with growth of load. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Fuzzy clustering   Fuzzy distance measurement   Multi-objective programming   Investment selection  

摘要： This paper presents a new fuzzy clustering approach based on an efficient fuzzy distance measurement and multi-objective mathematical programming. As the human intuitions implies, it is not rational to measure the distance between two fuzzy clusters by a crisp measurement. Unfortunately, most of the existing fuzzy clustering approaches, consider the distance between two fuzzy clusters as a crisp value. This will yield a rounding error and is assumed a pitfall. In this paper, an efficient fuzzy distance measurement is developed in order to measure distance between multi-dimensional fuzzy clusters as a fuzzy measure. The triangle fuzzy numbers (TFNs) are used to develop the applicable fuzzy clustering approach. Then, multi-objective mathematical programming is utilized to optimize the center, and left and right spreads of fuzzy clusters which are calculated as TFNs. More formally, the advantages of proposed fuzzy clustering in comparison with existing procedure is (a) developing an efficient fuzzy distance measurement, and (b) optimizing the center and spread of the fuzzy clusters using multi-objective mathematical programming. An illustrative random simulated instance is supplied in order to present the mechanism and calculations of the proposed fuzzy clustering approach. The performance of proposed fuzzy clustering approach is compared with an existing Fuzzy C-means approach in the literature on several benchmark instances. Then, the Error Ratio is defined to compare the performance of both methods and comprehensive statistical analysis and hypothesis test are accomplished to test the performance of both methods. Finally, a real case study, called group decision making multi-possibility multi-choice investment partitioning problem, is discussed in order to illustrate the efficacy and applicability of the proposed approach in real world problems. The proposed approach is straightforward, its quality is as well as existing approach in the literature and its results ar

关键词： cable industry   mathematical programming   production scheduling   simulated annealing   variable neighborhood search  

摘要： This paper addresses an application of production scheduling problems in cable industry. In cases where the size and color of cable are changed, the cable industry is classified as a multiproduct, mass production system. Two different mathematical programming models based on continuous time representation are proposed for a case study on the scheduling problem of the cable industry to minimize the total cost including setup cost, operating cost, and inventory holding cost. As the solution methodology, different grouping policies, for example, grouping cables of the same size and grouping cables of the same color are proposed. Then different metaheuristic methods based on simulated annealing and variable neighborhood search algorithms are applied to minimize the total cost of proposed solutions. Finally, the solution with the smallest total cost is selected as the production schedule of the case study, while Xpress solver could not provide any feasible solution for the mathematical models in the problem size of case study.

关键词： Nano-Y2O3 dispersed ferritic alloys   Neural network   Genetic algorithm   Consolidation temperature   Chromium  

摘要： This paper demonstrates the effects of chromium content and consolidation temperature on nano-Y2O3 dispersed ferritic alloys 83.0Fe-13.5Cr-2.0AI-0.5Ti (alloy A), 79.0Fe-17.5Cr-2.0Al-0.5Ti (alloy B), 75.0Fe-21.5Cr-2.0Al-0.5Ti (alloy C) and 71.0Fe-25.5Cr-2.0Al-0.5Ti (alloy D) each containing 1% Y2O3 (all in wt%) using mathematical modelling. An artificial neural network model is developed for the (a) physical properties (density and porosity) and (b) mechanical properties (hardness, Young's modulus, and compressive strength) of alloy. A three-layer neural network model was developed, and the genetic algorithm (an evolutionary algorithm) is applied for training the neural network. The results reveal that the proposed genetic-algorithmbased model performed better than the traditional neural network model and the linear regression model for modelling of the physical and mechanical parameters of chromium alloys. The simulated maps of the physical and mechanical properties of alloys were generated against the processing parameters, i.e., consolidation temperature and Cr (wt.%). The developed model can be used for optimization of the mechanical alloying process for synthesis of nano-Y2O3 dispersed ferritic alloys. (C) 2015 Elsevier B.V. All rights reserved.

关键词： NONFICTION   POPULAR works in mathematics  

关键词： Metaheuristics   Scheduling   Evolutionary computations   Mathematical modeling   Decision making  

摘要： Dynamic flexible job shop scheduling is of significant importance to the implementation of real-world manufacturing systems. In order to capture the dynamic and multi-objective nature of flexible job shop scheduling, and provide different trade-offs among objectives, this paper develops a multi-objective evolutionary algorithm (MOEA)-based proactive reactive method. The novelty of our method is that it is able to handle multiple objectives including efficiency and stability simultaneously, adapt to the new environment quickly by incorporating heuristic dynamic optimization strategies, and deal with two scheduling policies of machine assignment and operation sequencing together. Besides, a new mathematical model for the multi-objective dynamic flexible job shop scheduling problem (MODFJSSP) is constructed. With the aim of selecting one solution that fits into the decision maker's preferences from the trade-off solution set found by MOEA, a dynamic decision making procedure is designed. Experimental results in a simulated dynamic flexible job shop show that our method can achieve much better performances than combinations of existing scheduling rules. Three MOEA-based rescheduling methods are compared. The modified epsilon-MOEA has the best overall performance in dynamic environments, and its computational time is much less than two others (i.e., NSGA-II and SPEA2). Utilities of introducing the stability objective, heuristic initialization strategies and the decision making approach are also validated. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Discrete-time algebraic Riccati equation   Doubling algorithm   Large-scale problem  

摘要： We consider the numerical solution of large-scale discrete-time algebraic Riccati equations. The doubling algorithm is adapted, with the iterates for A not computed explicitly but recursively. The resulting algorithm is efficient, with computational complexity and memory requirement proportional to the size of the problem, and essentially converges quadratically. An error analysis, on the truncation of iterates, and some numerical results are presented. (C) 2014 Elsevier B.V. All rights reserved.

关键词： life cycle cost   optimisation models   infrastructure planning   evolutionary computations   network analysis   rehabilitation  

摘要： Civil infrastructure assets require continuous renewal (repair, rehabilitation or replacement) actions to modernise the inventory and sustain its operability. Allocating limited renewal funds among numerous asset components, however, represents a complex optimisation problem. Earlier efforts using genetic algorithms (GAs) could optimise small size problems yet exhibiting steep degradation in solution quality as problem size increases. Even by applying sophisticated mechanisms such as 'segmentation' to improve the performance of GAs, large processing time hinders the practicality of the algorithm for large-scale problems. This article, therefore, aims at improving both processing speed and solution quality for very large-scale problems (up to 50,000 assets). The article develops optimisation models using an advanced modelling tool (GAMS/CPLEX), and compares its results with GAs on three different model formulations. Both approaches proved to be beneficial, yet the advanced mathematical approach showed superior performance.

关键词： 数字图像   碎纸复原   匹配度  

摘要： 传统的拼接复原工作需由人工完成,准确率较高,但效率很低。针对该问题,借助数字图像处理技术,建立了关于图片匹配度函数的优化模型,依据穷举思想设计了求解算法,可大幅提高复原效率,但在处理复杂问题时,准确性有所下降,需要一定的人工介入。通过对复原后图片的验证结果可知,碎纸片复原拼接模型具有可行性。

关键词： 车辆路径规划   数学模型   启发式算法   精确算法  

摘要： 车辆路径规划问题（Vehicle Routing Problem，VRP）是一项研究热点。在运输过程中，对车辆进行合理的路径规划可以在满足运输要求的基础上最大程度地节约人力物力，降低运输成本。在对车辆路径规划的研究过程中，模型和算法起着关键性作用。目前已有的模型和算法还存在一些不足。为此，对车辆路径规划问题的数学模型和算法进行了探讨。