基于混合蛙跳算法的异地分布式协同开发的任务分配优化  

Task assignment optimization for distributed cooperative development based on shuffled frog leaping algorithms

作　　者：周聪 姜继娇 殷茗[3] ZHOU Cong;JIANG Jijiao;YIN Ming(School of Management Northwestern Polytechnical University Xi’an 710072,China;Software and Microelectronics Northwestern Polytechnical University Xi’an 710072,China)

机构地区：[1]西北工业大学管理学院,陕西西安710072 [2]西北工业大学管理学院管理科学与工程系,陕西西安710072 [3]西北工业大学软件与微电子学院,陕西西安710072

出　　处：《管理工程学报》2020年第6期148-155,共8页Journal of Industrial Engineering and Engineering Management

基　　金：教育部人文与社会科学基金项目(16YJA630068、18YJA630043);航空科学基金资助项目(2016ZG53071);陕西省自然科学基础研究计划项目(2018JM7008);西北工业大学研究生创意创新种子基金资助(ZZ2018036)。

摘　　要：异地分布式协同开发已经成为大型复杂产品开发策略的一部分,复杂产品在动态环境下,针对不同团队的技术水平、专业方向、所在的地理位置等外部条件进行实时任务分配这一问题,本文采用无约束化的编码方式并结合变异、交叉的遗传操作,建立基于混合蛙跳算法的异地分布式多团队开发环境中的任务分配模型。该模型,参考Scrum产品的开发框架对任务进行分解,以协同生产企业的敏捷性与其地理位置为优化目标,实现在异地分布式环境中的任务智能分配。通过模拟我国某飞机发动机任务分配的过程,验证算法的性能。结果表明,与原始的混合蛙跳算法相比,本文所提的改进混合蛙跳算法具有较好的全局搜索能力与求解的精度。Geographically distributed collaborative development has become part of the development strategy for large and complex products. Complex products are composed of multiple subsystems, and each subsystem involves multiple disciplines, which makes the complex interaction between large complex R&D product enterprises and the outside world. In different stages of complex product development, a single enterprise is often limited by technology and resources, and cannot complete the entire process of product development independently. This requires mutual cooperation between enterprises, resource sharing, and risk sharing. Geographically distributed collaborative development can integrate the resources of different geographies, enterprises, and teams to reduce risks, but it also brings about coordination and cooperation issues between geographically distributed teams. In response to this phenomenon, this paper studies the problem of task assignment for large and complex products in a geographically distributed agile development environment. This paper mainly does the following work: First, it proposes a task allocation optimization model for geographically distributed agile development based on hybrid shuffled frog-leaping algorithm. This model uses the scrum of scrums agile development model as the basic framework for the development and production of large and complex products, and decomposes the R&D and production tasks of complex products then takes the maximum agility and minimum geographic compactness of the enterprise of complex aviation products as the objective function. Second, the unconstrained coding method is used to encode the model solution, which the "cross" and "mutation" operators are introduced in the learning strategy of the hybrid shuffled frog-leaping algorithm to optimize the local and global search mechanism of the hybrid shuffled frog-leaping algorithm and improve the efficiency and convergence accuracy of the algorithm. Third, taking an aircraft engine R&D enterprise as an example, MATLAB softwa

关 键 词：复杂产品 异地分布式协同开发 混合蛙跳算法 敏捷性 

分 类 号：C935[经济管理—管理学]