A multiobjective model for maximizing fleet availability under the presence of flight and maintenance requirements

Every aircraft, military or civilian, must be grounded for maintenance after it has completed a certain number of flight hours since its last maintenance check. In this paper, we address the problem of deciding which available aircraft should fly and for how long, and which grounded aircraft should perform maintenance operations, in a group of aircraft that comprise a combat unit. The objective is to achieve maximum availability of the unit over the planning horizon. We develop a multiobjective optimization model for this problem, and we illustrate its application and solution on a real life instance drawn from the Hellenic Air Force. We also propose two heuristic approaches for solving large scale instances of the problem. We conclude with a discussion that gives insight into the behavior of the model and of the heuristics, based on the analysis of the results obtained.     

THE OPTIMALITY CONDITION AND DUALITY OF MULTIOBJECTIVE POSYNOMIAL GEOMETRIC PROGRAMMING

1IntroductionSinceitsinceptionbyZener[1'2JandDuf-fin[3.'1,geometricprogramminghasundergonerapiddevelopment,especiallyaftertheappear-anceofthefirstbookonthesubject['j.Multiob-jectivemathematicalprogrammingisalsoafast-developingsubject.Therehavebeenmanyachievementsinboththeoreticalandappliedas-pects['~'].Considerthemultiobjectiveprogrammingproblem:whereXcrR"(n>l)isaconstraintsetandf:X-R-(m>2)avectorobjectivefunction.WriteR7=(v6R'lv>o}iandletxbeasdefinedaParetoefficientsolutionof(VMP)ifxeXa…     

A multiobjective land development optimization model: the case of New Castle County,Delaware

This paper develops a multiobjective optimization model to consider transportation impacts of the future development of land. The output of the model is the best location and type of land use that has minimal negative transportation effects and uses the maximum available public transportation infrastructure. It provides tools for both planners and transportation engineers and enables them to consider different scenarios of possible policies and land development. Since multiple objectives and their nonlinear structures are considered, the model is solved using mixed integer nonlinear programming. The final results are shown in both tabular and graphical format. The effectiveness of the model is applied to the northern part of New Castle County, Delaware. The results show that the model successfully finds the best locations for both residential and commercial land uses in order to meet several criteria discussed in the paper.     

Multiobjective optimisation of bogie suspension to boost speed on curves

To improve safety and maximum admissible speed on different operational scenarios, multiobjective optimisation of bogie suspension components of a one-car railway vehicle model is considered. The vehicle model has 50 degrees of freedom and is developed in multibody dynamics software SIMPACK. Track shift force, running stability, and risk of derailment are selected as safety objective functions. The improved maximum admissible speeds of the vehicle on curves are determined based on the track plane accelerations up to 1.5?m/s². To attenuate the number of design parameters for optimisation and improve the computational efficiency, a global sensitivity analysis is accomplished using the multiplicative dimensional reduction method (M-DRM). A multistep optimisation routine based on genetic algorithm (GA) and MATLAB/SIMPACK co-simulation is executed at three levels. The bogie conventional secondary and primary suspension components are chosen as the design parameters in the first two steps, respectively. In the last step semi-active suspension is in focus. The input electrical current to magnetorheological yaw dampers is optimised to guarantee an appropriate safety level. Semi-active controllers are also applied and the respective effects on bogie dynamics are explored. The safety Pareto optimised results are compared with those associated with in-service values. The global sensitivity analysis and multistep approach significantly reduced the number of design parameters and improved the computational efficiency of the optimisation. Furthermore, using the optimised values of design parameters give the possibility to run the vehicle up to 13% faster on curves while a satisfactory safety level is guaranteed. The results obtained can be used in Pareto optimisation and active bogie suspension design problems.     

轴重与胎压对半刚性基层沥青路面动力响应影响理论研究

采用多目标参数评价方法,分析了车辆轴重和胎压对路面结构动力响应的影响,建立移动荷载下粘弹性层状体系动力学模型。结果发现,路面结构动力响应随着轴重和胎压的增加而增加,轴重和胎压对路面结构的动力响应具有耦合性。0.7 MPa胎压下,轴重达到250 kN时,面层底部弯拉应变和土基顶部竖向压应变均小于永久性路面结构设计指标,可作为校核指标;面层底部水平剪应变远大于层底弯拉应变,可作为半刚性基层沥青路面动态设计的主要设计指标。因此,提高面层与基层之间的粘结强度是提高半刚性基层沥青路面结构使用寿命的关键。     

基于交互式多目标遗传算法的混凝土桥面板维修优化

为了保证桥梁结构安全,并使维修效果最好,研究了如何确定桥面板最佳维修策略的问题。建立了桥面板维修的多目标优化模型。提出一种基于交互式遗传算法的维修策略优化方法,通过非精确偏好信息引导遗传搜索,使种群朝着多个目标的最佳综合性能进化。引入适应值共享方法增加种群的多样性,最终获得符合决策者偏好的解集。并通过算例进行了分析验证。结果表明,基于交互式多目标遗传算法的混凝土桥面板维修优化方法可以在有限的桥梁维修资源和良好的维修效果之间进行折衷,不仅获得一组比较理想的维修方法组合,还可以考虑决策者的个人倾向,降低了维修策略的选择难度,为桥梁管理者提供了有力的决策支持。     

对话型模糊多目标规划模型及求解方法

本文对对话型模糊多目标规划方法的以下几个方面进行了探讨：对话型方法中隶属函数和模型的构造；调整满意解的原理和方法；应用可能性理论求解模糊多目标规划的对话型方法；并给出了应用实例。     

信号控制模型中利益分配问题的研究

设计了一个平衡约束条件下信号控制与平衡网络设计组合问题的多目标规划模型，然后使用效用函数法将有双目标的上层优化问题转化为一个单目标优化问题．在这种情况下，该模型变成一个标准的双层规划模型。并利用全局优化方法模拟退火算法和惩罚函数法相结合求解．     

不可行集蚁群算法在铁路放射性物质载运中的应用

研究铁路货物运输中放射性物质的载运问题,目的是把安全运输与车辆的合理利用有机结合.以货物的客户要求期限与铁路运到期限之差的数学期望、铁路车辆的载重量利用率、装载货物的轻重搭配合理程度作为研究问题的3个目标;将装载货物运输指数限制、车辆标记载重限制、车辆载货容积限制、装载加固限制作为研究问题的约束条件,建立多目标规划模型.依据目标的重要性确定权向量,根据运输实际情况确定理想点,利用理想点法将多目标规划问题转化为单目标规划问题.运用基于不可行集的蚁群算法求得多目标规划问题的有效解.本文给出铁路放射性物质载运问题的计算实例,编程计算的结果证明蚁群算法具有较高的效率和可靠性.     

Multicriteria evaluation on accessibility‐based transportation equity in road network design problem

This paper investigates the performance of accessibility‐based equity measurements in transportation and proposes a multiobjective optimization model to simulate the trade‐offs between equity maximization and cost minimization of network construction. The equity is defined as the spatial distribution of accessibilities across zone areas. Six representative indicators were formulated, including GINI coefficient, Theil index, mean log deviation, relative mean deviation, coefficient of variation, and Atkinson index, and incorporated into an equity maximization model to evaluate the performance sensitivity. A bilevel multiobjective optimization model was proposed to obtain the Pareto‐optimal solutions for link capacity enhancement in a stochastic road network design problem. A numerical analysis using the Sioux Falls data was implemented. Results verified that the equity indicators are quite sensitive to the pattern of network scenarios in the sense that the level of equity varies according to the amount of overall capacity enhancement as well as the assignment of improved link segments. The suggested multiobjective model that enables representing the Pareto‐optimal solutions can provide multiple options in the decision making of road network design. Copyright © 2012 John Wiley & Sons, Ltd.