融合遗传蚁群算法的Web 服务组合研究

为了提高Web服务组合流程中服务选择技术的收敛性能,提出了一种基于遗传算法与蚁群算法相融合的多目标优化策略,用于解决基于QoS的Web服务组合问题。本文首先将Web服务组合的全局最优化问题转化为寻求一条QoS最优解的路径问题,并通过改进遗传算法得到蚁群算法中初始路径的信息素分布,再通过改进蚁群算法来求得最优解。仿真实验结果表明,该改进算法能在较少的进化代数下得到最优路径,提高了Web服务组合的快速全局搜索能力。     

混合智能算法在多约束优化问题中的应用*

提出了一种将蚁群算法、遗传算法和粒子种群优化融合的混合智能算法来解决多约束最优路径和QoS路由问题。采用蚁群算法进行寻径生成初始群体,利用遗传算法对路径进行优化,利用PSO算法来优化蚁群算法中的信息素,优势互补。仿真结果表明该算法是可行、有效的。     

改进蚁群算法的送餐机器人路径规划

蚁群算法拥有良好的全局性、自组织性、鲁棒性,但传统蚁群算法存在许多不足之处。为此,针对算法在路径规划问题中的缺陷,在传统蚁群算法的状态转移公式中,引入目标点距离因素和引导素,加快算法收敛性和改善局部最优缺陷。在带时间窗的车辆路径问题（vehicle routing problem with time windows,VRPTW）上,融合蚁群算法和遗传算法,并将顾客时间窗宽度以及机器人等待时间加入蚁群算法状态转移公式中,以及将蚁群算法的解作为遗传算法的初始种群,提高遗传算法的初始解质量,然后进行编码,设置违反时间窗约束和载重量的惩罚函数和适应度函数,在传统遗传算法的交叉、变异操作后加入了破坏-修复基因的操作来优化每一代新解的质量,在Solomon Benchmark算例上进行仿真,对比算法改进前后的最优解,验证算法可行性。最后在餐厅送餐问题中把带有障碍物的仿真环境路径规划问题和VRPTW问题结合,使用改进后的算法解决餐厅环境下送餐机器人对顾客服务配送问题。     

求解非连通图旅行商问题的改进遗传算法

为了克服传统遗传算法的早熟收敛问题,提出改进遗传算法。采用基于旅行商遍历城市顺序的染色体编码,结合随机法与贪心法生成初始种群,提高遗传效率。通过执行优先保留交叉和平移变异操作,引入局部邻域搜索,给出最优解是否满足非连通约束的判据。最后,实验结果验证了该算法的有效性。     

两阶段式的物流配送路径优化方法

根据组合优化理论,充分利用遗传算法、蚁群算法的优化点,提出了一种两阶段式的物流配送路径优化方法(GA-ACO)。利用遗传算法迅速找到物流配送路径优化问题的初始解,初始解生成蚁群算法的初始信息素分布,通过蚁群算法找到物流配送路径的最优方案。采用实例对GA-ACO的性能进行测试,测试结果表明,GA-ACO可以获得较好的物流配送路径优化方案,是一种高效率、鲁棒性好的物流配送路径优化问题求解方法。     

QoS全局最优的多目标Web服务选择算法*

针对现有方法的不足,提出一种基于QoS全局最优的多目标动态Web服务选择算法。在给出动态服务组合模型的基础上,以“抽象服务规划”为输入,以用户的非功能性需求为全局约束,将动态服务选择问题转换为一个带QoS约束的多目标服务组合优化问题;利用多目标蚁群算法,多个目标函数被同时优化并产生一组满足约束条件的Pareto优化解。通过运用实验与基于多目标遗传算法的Web服务选择算法进行对比,证明了该方法的可行性和有效性。     

基于RRT*的母线布线路径规划算法

针对母线布线设计繁杂,低效,耗时成本高的问题。对工程中母线布线设计的约束与优化目标进行了研究总结,提出了一种基于快速扩展随机树算法(RRT*)的母线布线路径规划算法。在传统的RRT*算法的基础上,通过引入中间点（corner点）的方式改变已生成路径到随机点的扩展方式,使生成路径符合母线的走向限制,实现了初始路径的生成。同时在初始路径生成过程中采取贪心的优化策略,获得弯头数量最少且满足约束的路径。仿真结果表明,相较于传统的RRT*路径规划算法,本文提出的算法可以很好的满足母线的各项布线要求,为母线的自动布线问题提供了一个新方法。     

基于蚁群遗传混合算法的QoS组播路由

具有延迟、延迟抖动、带宽、丢包率等服务质量约束的组播路由问题具有NP完全的复杂度。基于蚁群优化算法和遗传算法,提出解决QoS约束组播路由问题的混合算法。利用遗传算法和蚁群优化算法各自的优点,使用蚁群优化算法选择种群,遗传算法优化蚂蚁遍历所得到的解。仿真实验结果表明,该算法可满足各个约束条件,且全局寻优性能好,能够满足网络服务质量要求。     

改进蝴蝶优化算法在护理人员路径规划与调度中的应用

针对养老资源利用不充分的问题,提出一种同时考虑成本和顾客满意度的医疗护理人员的路径规划与调度,基于服务成本、顾客满意度两个方面建立多目标多家庭护理企业的路径优化模型。根据建立的优化模型,提出一种改进后的蝴蝶优化算法进行求解,将快速非支配排序与蝴蝶优化算法相结合,从而提高对最优解集的搜索效率,使得“蝴蝶”能更好地追随最优“蝴蝶群”,提高收敛速度和保持解的多样性。实验结果表明,所提出的优化模型和算法能够兼顾成本和顾客满意度两个目标,得出最优解集。     

基于QoS的多目标服务组合算法

服务组合优化问题是当前服务计算领域的研究热点之一。针对现有优化技术将多个约束条件转化为单一优化目标难以处理多目标问题的不足,提出了一种基于多目标优化的粒子群算法,将多约束服务组合选取问题转化成为一种带约束的多目标优化问题,利用粒子群算法的智能优化原理,通过同时优化多个服务质量参数,产生一组最优非劣解集。实验结果表明了算法在处理多目标优化问题的有效性。     

异步粒子群优化算法在QoS组播路由中的应用

QoS组播路由问题是一个非线性的组合优化问题,已证明了该问题是NP完全问题。为适应下一代IP网络对实时信息传输的要求,在异步模式粒子群优化算法基础上,给出包含延迟、延迟抖动、带宽、丢包率和最小花费5个约束条件在内的QoS组播路由算法。该算法首先给出数学模型,设计适应度函数,再给出受限的网络模型,通过粒子群优化(PSO)算法最大化适应度函数来求解最优Steiner树。算法仿真实验结果表明:与遗传算法和同步模式的粒子群优化算法相比,该算法有较好的收敛速度和寻优效果。     

A GRASP × ILS for the vehicle routing problem with time windows,synchronization and precedence constraints

Efficient use of resources while ensuring quality services points the attention of Home Health Care structures (HHC). HHC structures propose keeping at home patients who do not necessarily need full hospitalization, and enabling people who suffered serious illnesses to follow the care from their own home. Habitually, asked services have to be performed at specific times, and may require the intervention of several qualified caregivers related by precedence constraints. These structures have the concern to reduce product consumption costs, limit losses and provide high quality services. Their main budgetary item is defined by the personal salary, which is incompressible. So, costs should be reduced on other posts. In this context, personal travel cost has a major importance in the spending of the institutions, which seems necessary to optimize. Moreover, patient satisfaction is also a significant criterion in improving the service quality of such structures. Therefore, developing an effective caregivers planning require the use of optimization methods and decision tools. In this article, this issue is modeled as a particular variant of vehicle routing problem with time windows and timing constraints, where some patients ask for more than one visit simultaneously or in a given priority order, called as the VRPTW-SP. Timing constraints handled in this paper make the problem realistic that are more difficult to solve than VRPTW. The VRPTW-SP is a challenging and novel optimization problem, whose objective is the minimization of the caregivers travel cost added to the non preferences toward caregivers. To solve this problem, a Mixed Integer Linear Program, a greedy heuristic, two local search strategies and three metaheuristics are proposed, one being a hybridization of the two others. Experiments are conducted on new instances derived from the literature. As the metaheuristics share the same components the positive contribution of the hybridization is proved on the VRPTW-SP by statistical tests.     

带度约束的最小直径应用层多播路由问题的启发式遗传算法

由于IP多播难以在因特网环境中配置，应用层多播作为IP多播的一种替代方案得到越来越多的研究。从网络设计的角度来看，应用层多播在网络代价模型及路由策略方面与传统的IP多播有很大区别。本文研究了带度约束的最小直径应用层网络多播路由问题，提出了解决该问题的启发式遗传算法。通过大量仿真实验，我们对比分析了两种贪婪算法法和遗传算法的性能。实验显示，启发式遗传算法具有较好的性能。     

一种带约束的多目标服务质量路由算法

多约束服务质量(QoS)路由是要求在多个约束条件下计算满足所有独立限制条件的可行路径．将这种NPC问题转化为一种带约束条件的多目标优化问题，根据多目标遗传算法的智能优化原理，提出一种多目标QoS路由算法来产生一组最优非劣路由．理论分析和实验结果表明，使用带约束的多目标遗传算法是解决多约束QoS路由的有效途径，能对提高网络性能起到重要作用．     

一种满足时延和时延抖动约束的多播路由算法

多播路由已有广泛的应用,但对于实时多播应用,多播路由的同时必须提供QoS保证。为此,论文研究带有时延和时延抖动约束的多播路由问题,通过对Dijkstra最短路径算法的扩展,提出一个快速有效的满足时延和时延抖动约束的多播路由算法EDDVCMR。实验结果表明,对解决带有时延和时延抖动约束的多播路由问题,该算法与DVMA算法相比,有高出7%的求解成功率,同时,算法执行的CPU时间减少36%。     

A QoS Based Reliable Routing Mechanism for Service Customization

Due to the rapid development of the Internet technology such as 5G/6G and artificial intelligence, more and more new network applications appear. Customers using these applications may have different individual demands and such a trend causes great challenges to the traditional integrated service and routing model. In order to satisfy the individual demands of customers, the service customization should be considered, during which the cost of Internet Service Provider (ISP) naturally increases. Hence, how to reach a balance between the customer satisfaction and the ISP profit becomes vitally important. Targeting at addressing this critical problem, this work proposes a service customization oriented reliable routing mechanism, which includes two modules, that is, the service customization module and the routing module. In particular, the former (i.e., the service customization module) is responsible for classifying services by analyzing and processing the customer’s demands. After that, the IPv6 protocol is used to implement the service customization, since it naturally supports differentiated services via the extended header fields. The latter is responsible for transforming the customized services into specific routing policies. Specifically, the Nash equilibrium based economic model is firstly introduced to make a perfect balance between the user satisfaction and the ISP profits, which could finally produce a win-win solution. After that, based on the customized service policies, an optimized grey wolf algorithm is designed to establish the routing path, during which the routing reliability is formulated and calculated. Finally, the experiments are carried out and the proposed mechanism is evaluated. The results indicate that the proposed service customization and routing mechanism improves the routing reliability, user satisfaction and ISP satisfaction by about 8.42%, 15.5% and 17.75% respectively compared with the classical open shortest path first algorithm and the function learning based algorithm.     

基于免疫遗传算法的多约束QoS路由选择算法

该文针对多约束Qos路由选择问题，将其转化为一个多约束赋权图最短路径问题，选择费用、带宽、时延、丢失率为Qos参数。设计了一个基于免疫遗传算法的Qos路由选择算法，该算法主要利用生物免疫机制中的抗原识别、抗原记忆和抗体的抑制、促进作用来控制收敛方向，促进快速求解。实验表明本文提出的算法具有较好的性能，大幅度地提高Qos路由选择的效率。     

电子中介中的交易匹配研究

研究电子中介中的匹配问题,提出了电子中介处理多属性商品交易时双方的满意度函数.以最大化双方满意度为目标,建立了多个买家和多个卖家各交易一件同类商品的多目标匹配优化模型,提出一种求解单目标的优先贪婪算法.3种算法的仿真实验表明,优先贪婪算法比精确算法损失匹配数量约8.0%,节约时间约31.6%;比标准贪婪算法提高匹配数量约2.7%,节约时间约36.3%.     

An efficient VLSI switch-box router

A tool for switch-box routing that can route regions with cyclic constraints and with terminals on three or four sides is presented. A divide-and-conquer algorithm is used to explore the greedy channel routing idea, using techniques such as routing area partitioning, dynamic routing strategies, and sweeping concurrent bidirectional columns. The routing area is decomposed into three parts by two special lines cut parallel, making routing easier. The algorithm completely routes Burstein's switch-box problem and with an extension also routes the Deutsch channel example in 19 tracks     

一种基于蚁群系统的组播路由算法

提出一种基于蚁群系统的求解QoS(quality of service)组播路由问题的新算法.算法中控制参数及路由选择策略根据迭代过程所处的不同阶段自适应调整.综合考虑QoS路由中所有约束条件的同时，也充分考虑各个约束自身的独立特性.实验证明算法所得的解不但较高程度地满足各个约束条件,而且多样性好、收敛速度快,能满足实际网络服务质量要求.