基于两层架构协调的应急物资分配与车辆调度集成优化方法

针对突发事件下的应急物资调运问题，考虑了多个地区同时受灾以及多个出救点需要对其进行救灾并且各出救点的运力有限的情况，以最小化总的车辆运输费用，最大化救灾效率、各受灾点的救灾满意度，以及各受灾点得到救助的公平性为目标，建立了该问题的多目标混合整数非线性规划模型，并提出了一个基于两层架构协调的迭代式遗传算法进行求解。基于仿真数据的实验结果证明了所提出的模型和算法的有效性。     

Dually sustainable urban mobility option: Shared-taxi operations with electric vehicles

Electric vehicles (EVs) are energy efficient and often presented as a zero-emission transport mode to achieve long-term decarbonization visions in the transport sector. The implementation of a sustainable transportation environment through EV utilization, however, requires the addressing of certain cost and environmental concerns such as limited driving range and battery-charging issues before its full potential can be realized. Nevertheless, a specific type of use of EVs, namely in taxi services, may elicit positive public opinion, as it promises a commitment toward sustainability in urban life. In light of this, this study proposes an integrated approach that combines EV operation with a conceptual design for shared-ride taxi services. As some productivity loss may be naturally expected due to the time spent in charging, it is important to look at whether such performance loss from the passenger and system standpoints can be offset with ingenuity in operational design. In this study, an EV taxi charge-replenishing scheme that can be coupled with a real-time taxi-dispatch algorithm is designed. The proposed EV charging schemes for taxi services are studied via simulations and the effects of the limited driving range and battery-charging details are examined from a system performance viewpoint. The simulation study also reveals illustrative results on the impact of the EV taxi fleet's operation on the charging system. Next, a real-time shared-taxi operation scheme that allows ride sharing with other passengers is proposed to maximize the operational efficiency. The simulation results suggest that the shared-taxi concept can be a viable option to improve on the limitations caused by EV operation. In addition, the importance of projected charging demands and queue delays at different charging locations are also addressed. Some limitations and a future research agenda are also discussed.     

基于SBO-PP模型的水资源可持续发展能力评价模型及应用

为利用投影寻踪(PP)技术科学,客观评价区域水资源可持续发展能力,基于生态环境、水资源和经济社会因素选取20个指标构建区域水资源可持续发展能力评价指标体系。利用新型仿生群体智能算法——凉亭鸟优化(SBO)算法优化PP技术最佳投影方向,提出SBO-PP水资源可持续发展能力评价模型,并构建灰狼优化(GWO)算法-PP模型、人工蜂群(ABC)算法-PP模型、差分进化(DE)算法-PP模型、地理生物学优化(BBO)算法-PP模型、粒子群优化(PSO)算法-PP模型作对比,以云南省2006—2015年及2020年水资源可持续发展能力评价为例进行实例研究。结果表明:SBO算法优化PP技术获得的适应度值优于GWO、ABC、DE、BBO和PSO算法,具有较好的求解精度、稳健性能和极值寻优能力。SBO-PP模型对云南省2006—2007年水资源可持续发展能力评价为"较差",2008—2015年评价为"中等",2020年评价为"较强"。     

A network approach to modeling the multi-echelon spare-part inventory system with backorders and interval-valued demand

A multi-echelon inventory system implies the existence of a hierarchy of stocking locations, and the dependence and interaction between them. We consider a multi-echelon, spare-part inventory management problem with outsourcing and backordering. The problem is characterized by deterministic repair time/cost, and supply and demand that lie within prescribed intervals and that vary over time. The objective is to minimize the total inventory and transportation costs. We develop a network model for problem analysis and present a network flow algorithm for solving the problem. We prove that the Wagner-Whitin property, known for the lot-sizing problem, can be extended to the spare-part inventory management problem under study.     

How effective are heuristic solutions for electricity planning in developing countries

Heuristic algorithms have been widely used to provide computationally feasible means of exploring the cost effective balance between grid versus off grid sources for universal electrification in developing countries. By definition in such algorithms however, global optimality is not guaranteed. We present a computationally intensive but globally optimal mixed integer non-linear programming (MINLP) model for electricity planning and use it in a Monte Carlo simulation procedure to test the relative performance of a widely used heuristic algorithm due to [28]. We show that the overall difference in cost is typically small suggesting that the heuristic algorithm is generally cost effective in many situations. However we find that the relative performance of the heuristic algorithm deteriorates with increasing degree of spatial dispersion of unelectrified settlements, as well as increasing spatial remoteness of the settlements from the grid network, suggesting that the effectiveness of the heuristic algorithm is context specific. Further, we find that allocation of off grid sources in the heuristic algorithm solution is often significantly greater than in the MINLP model suggesting that heuristic methods can overstate the role of off-grid solutions in certain situations.     

Estimation of interregional input–output table using hybrid algorithm of the RAS method and real-coded genetic algorithm

In this paper, we propose a method for improving the accuracy of the estimation of interregional input–output tables, by combining the RAS method and the real-coded Genetic Algorithm (GA); these are simple representative methods for the estimation of an interregional input–output table. By comparing the performance evaluation results obtained using the proposed method, the RAS method, and Simulated Annealing, we verified that the combination of the genetic algorithm and the RAS method can enhance the estimation accuracy of an interregional input–output table. In addition, performance is further enhanced by adjusting GA parameters.     

基于遗传算法轿车焊装车间车辆路径优化

遗传算法是一种模拟自然进化过程搜索最优解的方法。通过建立某轿车焊装车间车辆路径问题数学模型,然后利用遗传算法求解该问题,最后在Matlab软件中进行编程求解,有效地求解出问题的最优解或近似最优解。     

B2C电子商务中带退货的多配送站点车辆路径优化问题研究

研究了一个带退货的多配送站点车辆路径优化问题,建立了求解该问题的0-1整数规划模型,以实现各个配送站点在给他们客户配送货物的同时,沿途取回这些客户的退货,以节约运输成本的目的。设计了一种新的解的表示方法和邻域变换,以此为基础构造出直接求解多配送站点车辆路径优化问题的禁忌搜索算法,在该禁忌搜索算法中首先通过一个启发式算法求得了0-1整数规划模型的一个较好的初始可行解,从而提高了禁忌搜索算法的收敛速度及性能,最后通过例子对禁忌搜索算法及其性能进行了说明。     

考虑地产价格的多目标物流配送中心选址模型与求解

首先对传统的配送中心选址模型进行改进,引入地产价格因素,以建设投资成本与货物运输费用最小为目标,建立多目标选址模型。其次,利用理想点的适应度计算方法将多目标问题转化为单目标问题进行遗传算法的求解。最后,以某企业在城市的物流配送中心选址为例,对模型进行应用,算例结果验证了模型的实用性与有效性。     

基于遗传算法的油料装备维修保障资源调度研究

通过对战时油料装备维修保障资源的调度分析,利用遗传算法建立了数学模型并进行了实例仿真,在资源调度效益最佳的基础上得出了相应的维修资源调度方案。