针对物流配送需求大、“最后一公里”交付困难等问题,提出带有动态能耗约束的多车辆与多无人机协同配送问题,并以最小化配送时间为目标建立混合整数规划模型(MIP).为解决该问题,设计K-means聚类和最近邻协同的初始解生成算法,并提出基...针对物流配送需求大、“最后一公里”交付困难等问题,提出带有动态能耗约束的多车辆与多无人机协同配送问题,并以最小化配送时间为目标建立混合整数规划模型(MIP).为解决该问题,设计K-means聚类和最近邻协同的初始解生成算法,并提出基于问题领域知识的自适应大规模邻域搜索算法(adaptive large neighborhood search,ALNS).在不同规模算例上的实验结果表明,所提出的算法相比于模拟退火算法、变邻域搜索算法和遗传算法在求解质量和求解效率方面都具有一定的优势,求解质量分别平均提升23.8%、23.3%和5.7%,表明ALNS较对比算法能够更好地平衡全局搜索和局部搜索.此外.灵敏度分析实验表明,无人机载重能力和无人机续航能力是影响包裹配送时间的两个关键因素.展开更多
Large-scale centralized exploitation of intermittent wind energy resources has become popular in many countries.However,as a result of the frequent occurrence of largescale wind curtailment,expansion of corresponding ...Large-scale centralized exploitation of intermittent wind energy resources has become popular in many countries.However,as a result of the frequent occurrence of largescale wind curtailment,expansion of corresponding transmission projects has fallen behind the speed at which installed wind capacity can be developed.In this paper,a coordinated planning approach for a large-scale wind farm integration system and its related regional transmission network is proposed.A bilevel programming model is formulated with the objective of minimizing cost.To reach the global optimum of the bi-level model,this work proposes that the upper-level wind farm integration system planning problem needs to be solved jointly with the lower-level regional transmission planning problem.The bi-level model is expressed in terms of a linearized mathematical problem with equilibrium constraints(MPEC)by Karush-KuhnTucker conditions.It is then solved using mixed integer linear programming solvers.Numerical simulations are conducted to show the validity of the proposed coordinated planning method.展开更多
Unmanned aerial vehicle（UAV） resource scheduling means to allocate and aggregate the available UAV resources depending on the mission requirements and the battlefield situation assessment.In previous studies,the mod...Unmanned aerial vehicle（UAV） resource scheduling means to allocate and aggregate the available UAV resources depending on the mission requirements and the battlefield situation assessment.In previous studies,the models cannot reflect the mission synchronization;the targets are treated respectively,which results in the large scale of the problem and high computational complexity.To overcome these disadvantages,a model for UAV resource scheduling under mission synchronization is proposed,which is based on single-objective non-linear integer programming.And several cooperative teams are aggregated for the target clusters from the available resources.The evaluation indices of weapon allocation are referenced in establishing the objective function and the constraints for the issue.The scales of the target clusters are considered as the constraints for the scales of the cooperative teams to make them match in scale.The functions of the intersection between the ＂mission time-window＂ and the UAV ＂arrival time-window＂ are introduced into the objective function and the constraints in order to describe the mission synchronization effectively.The results demonstrate that the proposed expanded model can meet the requirement of mission synchronization,guide the aggregation of cooperative teams for the target clusters and control the scale of the problem effectively.展开更多
In order to facilitate the scientific management of large-sized shipping companies, fleet planning under complicated circumstances has been studied. Based on multiple influencing factors such as the techno-economic st...In order to facilitate the scientific management of large-sized shipping companies, fleet planning under complicated circumstances has been studied. Based on multiple influencing factors such as the techno-economic status of ships, the investment capacity of company, the possible purchase of new ships, the buying/selling of second-hand vessels and the chartering/renting of ships, a mixed-integer programming model for fleet planning has been established. A large-sized shipping company is utilized to make an empirical study, and Benders decomposition algorithm is employed to test the applicability of the proposed model. The result shows that the model is capable for multi-route, multi-ship and large-scaled fleet planning and thus helpful to support the decision making of large-sized shipping companies.展开更多
文摘针对物流配送需求大、“最后一公里”交付困难等问题,提出带有动态能耗约束的多车辆与多无人机协同配送问题,并以最小化配送时间为目标建立混合整数规划模型(MIP).为解决该问题,设计K-means聚类和最近邻协同的初始解生成算法,并提出基于问题领域知识的自适应大规模邻域搜索算法(adaptive large neighborhood search,ALNS).在不同规模算例上的实验结果表明,所提出的算法相比于模拟退火算法、变邻域搜索算法和遗传算法在求解质量和求解效率方面都具有一定的优势,求解质量分别平均提升23.8%、23.3%和5.7%,表明ALNS较对比算法能够更好地平衡全局搜索和局部搜索.此外.灵敏度分析实验表明,无人机载重能力和无人机续航能力是影响包裹配送时间的两个关键因素.
基金supported in part by the National High Technology Research and Development Program of China(No.2012AA050208)National Natural Science Foundation of China(No.51177043)111 Project(No.B08013).
文摘Large-scale centralized exploitation of intermittent wind energy resources has become popular in many countries.However,as a result of the frequent occurrence of largescale wind curtailment,expansion of corresponding transmission projects has fallen behind the speed at which installed wind capacity can be developed.In this paper,a coordinated planning approach for a large-scale wind farm integration system and its related regional transmission network is proposed.A bilevel programming model is formulated with the objective of minimizing cost.To reach the global optimum of the bi-level model,this work proposes that the upper-level wind farm integration system planning problem needs to be solved jointly with the lower-level regional transmission planning problem.The bi-level model is expressed in terms of a linearized mathematical problem with equilibrium constraints(MPEC)by Karush-KuhnTucker conditions.It is then solved using mixed integer linear programming solvers.Numerical simulations are conducted to show the validity of the proposed coordinated planning method.
文摘Unmanned aerial vehicle（UAV） resource scheduling means to allocate and aggregate the available UAV resources depending on the mission requirements and the battlefield situation assessment.In previous studies,the models cannot reflect the mission synchronization;the targets are treated respectively,which results in the large scale of the problem and high computational complexity.To overcome these disadvantages,a model for UAV resource scheduling under mission synchronization is proposed,which is based on single-objective non-linear integer programming.And several cooperative teams are aggregated for the target clusters from the available resources.The evaluation indices of weapon allocation are referenced in establishing the objective function and the constraints for the issue.The scales of the target clusters are considered as the constraints for the scales of the cooperative teams to make them match in scale.The functions of the intersection between the ＂mission time-window＂ and the UAV ＂arrival time-window＂ are introduced into the objective function and the constraints in order to describe the mission synchronization effectively.The results demonstrate that the proposed expanded model can meet the requirement of mission synchronization,guide the aggregation of cooperative teams for the target clusters and control the scale of the problem effectively.
基金the Doctoral Programs Foundation ofMinistry of Education of China(No.20102125110002)
文摘In order to facilitate the scientific management of large-sized shipping companies, fleet planning under complicated circumstances has been studied. Based on multiple influencing factors such as the techno-economic status of ships, the investment capacity of company, the possible purchase of new ships, the buying/selling of second-hand vessels and the chartering/renting of ships, a mixed-integer programming model for fleet planning has been established. A large-sized shipping company is utilized to make an empirical study, and Benders decomposition algorithm is employed to test the applicability of the proposed model. The result shows that the model is capable for multi-route, multi-ship and large-scaled fleet planning and thus helpful to support the decision making of large-sized shipping companies.
