The two-echelon capacitated electric vehicle routing problem with battery swapping stations: Formulation and efficient methodology

In this paper, we present a two-echelon capacitated electric vehicle routing problem with battery swapping stations (2E-EVRP-BSS), which aims to determine the delivery strategy under battery driving range limitations for city logistics. The electric vehicles operating in the different echelons have different load capacities, battery driving ranges, power consumption rates, and battery swapping costs. We propose an integer programming formulation and a hybrid algorithm that combines a column generation and an adaptive large neighborhood search (CG-ALNS) to solve the problem. We conducted extensive computational experiments, demonstrate the applicability of the proposed model, and show the efficiency of the CG-ALNS algorithm. In addition, we explore the interplay between battery driving range and the effectiveness of vehicle emission reduction through sensitivity analysis.     

The Speed-Gradient Algorithm in the Inverse Stoker Problem for a Synchronous Electric Machine

The problem of control of the number of cycle slippings of an electric machine rotor by means of an external moment is considered by the example of a simple mathematical model. The speed-gradient method with the objective function determined by the oscillation energy function is applied to solve this problem. The use of quite a small control is a feature of this approach, which helps to save energy. We have developed an algorithm to control oscillations of an electric machine rotor, so that the rotor performs a predetermined number of cycle slippings. The simulation results illustrate the efficiency of the suggested algorithm.     

Some models for water distribution systems

In this paper the results of our investigation of methods and algorithms for operative and dynamical control of water distribution systems are presented. Our investigation was directed to the distribution system equipped with a variety of components—pipes, consumers, valves and the inner water store (a reservoir) as the most important one. The final model of the optimization problem containing all necessary restrictions is so complex that it is impossible to solve it without some special techniques. In the presented study we propose a multilevel approach based on the idea of aggregation of the pipelines network. In the paper the method of determination of aggregated model of the network is presented. The usefulness of this method in the optimization of water supply systems is examined. Based on an aggregated network model one determines optimal strategies for control of pumping stations. The optimization model consists of a linear objective function and quadratic constraints. A nonlinear mixed integer programming problem which is solved by modified branch and bound method is obtained.     

Locating replenishment stations for electric vehicles: application to Danish traffic data

Environment-friendly electric vehicles have gained popularity and increased attention in recent years. The deployment of a network of recharging stations is essential given their limited travel range. This paper considers the problem of locating electronic replenishment stations for electric vehicles on a traffic network with flow-based demand. The objective is to optimize the network performance, for example to maximize the flow covered by a prefixed number of stations or to minimize the number of stations needed to cover traffic flows. Two integer linear programming formulations are proposed to model the problem. These models are tested on real-life traffic data collected in Denmark.     

三种类型汽车的能耗和使用成本的建模研究

本文对电动,传统,混合动力三种类型汽车的能耗和使用成本问题进行了建模、求解及分析．首先定义了电动汽车的能量利用率ηE。根据能量守恒将所有电量转换成汽油消耗量,而传统车型则直接反映到汽油的消耗上,混合动力汽车则综合电动汽车和传统汽车的能耗模型,从而统一能耗水平评价标准．这样,我们就得到了三种不同类型车的能耗模型再进行模型求解以此来分析比较三种类型车哪一种节能效果好．对电动汽车来说,使用成本主要包括驾驶维护成本、报废处理成本,而对传统汽车来说,使用成本主要包括驾驶维护成本、报废处理成本、环境成本和其他成本,混合动力汽车则结合二者使用成本．因此,根据不同车型使用成本类型建立相应的数学模型,按照建立的公式,可以得到电动汽车的使用成本LCC1、传统汽车的使用成本LCC2和混合动力汽车的使用成本LCC3,从而进行模型求解．     

考虑绕行特征的电动汽车快速充电站选址问题及自适应遗传算法

快速充电站选址是电动汽车运营的重要内容之一。本文考虑电动汽车用户会通过绕行一定距离对车辆进行充电这一特征,建立了一个以电动汽车快速充电站建站成本和旅客整体绕行成本之和最小的双层整数规划模型。本文首先给出了用于生成绕行路径集合的A^*算法,然后设计了一种包含局部迭代搜索的自适应遗传算法对该模型进行求解。为了测试算法性能,通过两个不同规模的算例图与已有求解FPLM问题的遗传算法进行了比较,数值试验部分证明了算法的正确性和有效性。最后引入浙江省的高速路网图,从建站成本和截流量两方面对电池续航里程带来的影响进行了相关的灵敏度分析。     

Parking Capacity and Pricing in Park'n Ride Trips: A Continuous Equilibrium Network Design Problem

In this paper we consider the problem of designing parking facilities for park'n ride trips. We present a new continuous equilibrium network design problem to decide the capacity and fare of these parking lots at a tactical level. We assume that the parking facilities have already been located and other topological decisions have already been taken.The modeling approach proposed is mathematical programming with equilibrium constraints. In the outer optimization problem, a central Authority evaluates the performance of the transport network for each network design decision. In the inner problem a multimodal traffic assignment with combined modes, formulated as a variational inequality problem, generates the share demand for modes of transportation, and for parking facilities as a function of the design variables of the parking lots. The objective is to make optimal parking investment and pricing decisions in order to minimize the total travel cost in a subnetwork of the multimodal transportation system.We present a new development in model formulation based on the use of generalized parking link cost as a design variable.The bilevel model is solved by a simulated annealing algorithm applied to the continuous and non-negative design decision variables. Numerical tests are reported in order to illustrate the use of the model, and the ability of the approach to solve applications of moderate size.     

考虑机器能耗的绿色作业车间调度问题

针对传统作业车间调度,在保证交货期的前提下,以机器能耗最小为目标研究带有关机/重启策略的绿色车间调度问题。首先建立数学规划模型,然后在遗传算法的框架下,根据问题特点提出了一种局部调整的解码方式,在排产时进行工序的移动并确定其开始加工时刻。最后进行小规模算例运算,验证数学规划模型的有效性,再利用算例对基于局部调整解码和顺序解码的遗传算法进行对比测试,结果表明提出的局部调整解码可以在降低机器能耗的同时提高求解效率。     

Charge depleting range dynamic strategy with power feedback considering fuel-cell degradation

A charge depleting range dynamic strategy considering the fuel-cell degradation is proposed for the plug-in fuel cell hybrid electric vehicles in this paper, to seek the excellent economy performance with various driving ranges. The proposed strategy is developed by means of incorporating an adaptive equivalent factor into equivalent consumption minimization strategy with power feedback control. Firstly, the mathematical modeling of the proposed strategy is formulated to adjust the equivalent factor corresponding to the battery state of charge, which may vary with the forthcoming trip distance to dominate the expected energy consumption. The fuel cell voltage decay rate is applied to the feedback control of the restricted fuel-cell power, which is designed as the degradation model of fuel cell and integrated with the strategy. Secondly, the realization process of the charge depleting range dynamic strategy with restricted power feedback control model is a new attempt to design the real-time control method. Finally, the proposed strategy is validated by a numerical model developed by using the MATLAB/Simulink software and its effectiveness was evaluated by comparing it with the equivalent consumption minimization strategy. A sensitivity analysis is also conducted to study the effects of different trip distances. The effectiveness of power feedback control in fuel cell durability is validated through a hardware-in-the-loop experiment. The verified results demonstrate the influence of the equivalent factor on the control process, which makes the proposed strategy possible to provide significant improvement in the economy performance and fuel-cell durability.     

A closed queuing maintenance network for automated manufacturing systems

This paper models an unreliable automated manufacturing system (AMS) by a closed queuing network. The AMS consists of a multi-stage network of automated work stations linked by a computer. A closed queuing algorithm is applied to determine the system availability under steady state for the AMS. This algorithm is then integrated into a cost optimization model. By applying the revised genetic algorithm, the optimal (or near-optimal) number of standby units and repair rates for the repair stations are derived by minimizing the total cost. The model is verified by the intuitive results from the sensitivity analysis. A numerical example is used to compare the revised genetic algorithm and the conventional genetic algorithm. The results show that the proposed revised algorithm leads to significant improvement in execution time and lower average total cost.     

Optimal routing in non-geostationary satellite ATM networks with intersatellite link capacity constraints

The trend toward broadband communications in space is foreseeable, and its features predestine ATM as the basic mode of operation. Some of the low and medium earth orbit satellite concepts make use of intersatellite links (ISLs) to provide global connectivity with minimal usage of terrestrial fixed network resources. Interconnecting neighbouring satellites with ISLs results in a partially meshed switching subnetwork in space. The ISLs have a time-varying distance or may even lose sight of each other. This feature of the ISL topology dynamics significantly increases the complexity of connection-oriented network operation and routing. We deal with the routing problem to minimize the virtual path connection handover rate and path delay in the time-varying ISL subnetwork topology with ISL capacity constraints. A heuristic algorithm is proposed to deal with this problem, which is based on Lagrangean relaxation and dynamic programming. When there is sufficient capacity at every ISL, the algorithm produces an optimal solution easily using only dynamic programming. For evaluation of our algorithm, some computational results have been presented. These results show that our optimization algorithm can produce a solution close to an optimal solution when there exist ISL capacity constraints.     

Primal-dual interior-point method for thermodynamic gas-particle partitioning

A mathematical model for the computation of the phase equilibrium and gas-particle partitioning in atmospheric organic aerosols is presented. The thermodynamic equilibrium is determined by the global minimum of the Gibbs free energy under equality and inequality constraints for a system that involves one gas phase and many liquid phases. A primal-dual interior-point algorithm is presented for the efficient solution of the phase equilibrium problem and the determination of the active constraints. The first order optimality conditions are solved with a Newton iteration. Sequential quadratic programming techniques are incorporated to decouple the different scales of the problem. Decomposition methods that control the inertia of the matrices arising in the resolution of the Newton system are proposed. A least-squares initialization of the algorithm is proposed to favor the convergence to a global minimum of the Gibbs free energy. Numerical results show the efficiency of the approach for the prediction of gas-liquid-liquid equilibrium for atmospheric organic aerosol particles.     

基于两阶段求解策略的动态电动车辆路径优化研究

由于政府对新能源汽车的补贴政策和市区对燃油车限行政策的实时,越来越多的物流公司在城市配送中广泛采用电动汽车。然而,电动车续航里程受限,需要在途充电或者换电,同时客户需求的动态性以及充/换电设施的排队等现实因素也应该被考虑。为此,提出了分阶段策略求解动态电动车辆路径优化问题,并建立了两阶段的EVRP模型。其中第一阶段针对静态客户建立了静态EVRP模型,第二阶段在设计了换电站及动态客户插入策略的基础上,建立了动态EVRP模型以路径更新策略。最后,设计改进的CW-TS混合启发式算法来求解静态模型,设计贪婪算法求解动态模型。实验结果表明,模型与算法具有较好的适用性和有效性。     

Design of a wind farm collection network when several cable types are available

In this article we consider a real-world problem submitted to us by the Hatch company. This problem consists of designing a collection network for a wind farm, assuming that the locations of the turbines and the potential cables are known, several cable types are available, and the cost of the energy that dissipates through the cables is known. We propose a mixed integer quadratic programme to model the network design problem and then linearize the quadratic programme because the latter is too difficult to solve using a standard mathematical programming software. We describe several classes of inequalities that strengthen the resulting mixed integer linear programme. Finally we use real-world data supplied by Hatch to carry out computational experiments with several versions of our model.     

Decomposition approximation of queueing-network control models with tree structures

We devise a decomposition approximation method for a general branching queueing network with service-rate controls. The decomposition method, which reduces and simplifies computation routines considerably, results from the conditions for monotone optimal control policies in induction arguments. We first isolate each branch of connected queues as a subnetwork and then link the subnetworks through branching nodes to approximate the optimal control policies for the global network. The numerical results for a wide class of cost models show that the approximated optimal policies from the decomposed problems are sufficiently close to the optimal policies of the global problem.     

时变路网条件下联合配送的开放式车辆路径问题

针对城市物流系统中的多物流中心联合配送问题,设计一种多物流中心处理方法共享物流资源;分析城市路网的时变特性,设计路段行驶时间计算方法;综合考虑客户需求、时间窗、车辆不同出发时间、油耗、碳排放与联合配送模式等因素,以总成本最小为目标构建联合配送的开放式时变车辆路径规划模型,设计改进蚁群算法求解;实验结果表明以上方法具有可行性与有效性。     

The research on optimization of auto supply chain network robust model under macroeconomic fluctuations

Considering the uncertainty of the macroeconomic environment, the robust optimization method is studied for constructing and designing the automotive supply chain network, and based on the definition of robust solution a robust optimization model is built for integrated supply chain network design that consists of supplier selection problem and facility location–distribution problem. The tabu search algorithm is proposed for supply chain node configuration, analyzing the influence of the level of uncertainty on robust results, and by comparing the performance of supply chain network design through the stochastic programming model and robustness optimize model, on this basis, determining the rational layout of supply chain network under macroeconomic fluctuations. At last the contrastive test result validates that the performance of tabu search algorithm is outstanding on convergence and computational time. Meanwhile it is indicated that the robust optimization model can reduce investment risks effectively when it is applied to supply chain network design.     

考虑交通流量和总成本的电动汽车充电站规划研究

针对目标区域充电桩规划需求问题,在对区域充电需求分析和充电站数量估算的基础上,利用以同心圆的圆周和圆心为站址的充电站选址方法,构建以俘获的车流量与充电站所有成本之比最大的数学规划模型.在此基础上,根据南昌市某区电动汽车数量,确定所需要的充电站数量为4~9个,并规划出六种方案,然后对每一种方案的规划目标值进行计算和比较,得出第三种方案即建设6个充电站为最优方案.研究结果有利于完善城市的交通网络,提升城市电动汽车的运营能力.     

带平衡约束的离散网络平衡设计问题的遗传算法

本文研究了带平衡约束的离散网络设计问题及其求解算法.模型中上层是一个离散网络设计的数学规划模型,采用遗传算法来求解.下层是采用变分不等式描述的用户平衡配流问题,利用对角化方法直接求解.通过实例对算法进行验证,结果表明该算法是有效的.     

Solving a vehicle routing problem by balancing the vehicles time utilization

Various vehicle routing problems (VRP) appear in the literature due to their important applications in the area of transportation and distribution.A VRP is characterized by the constraints that the involved factors must satisfy and by an optimality goal.In this paper, we develop a heuristic algorithm that

• (i)partitions suitably a distribution network into subnetworks. A single depot complies with every subnetwork, where a fleet of identical vehicles will start their itinerary. The nodes of the corresponding subnetwork are demand nodes that require a onetime visit by one only vehicle.
• (ii)Determine the routes of k vehicles, k=2,3,…, for every subnetwork so to minimize the visiting time of the corresponding demand nodes. Consequently the method computes the necessary vehicle number for each subnetwork so as to complete promptly the visiting requirement of all the demand nodes of the whole network. The main strategy of the algorithm for designing the vehicle routes consists of balancing the time utilization of the used vehicles. The paper is integrated by an application of the presented algorithm to the center of the city of Thessaloniki.