Group role assignment(GRA)is originally a complex problem in role-based collaboration(RBC).The solution to GRA provides modelling techniques for more complex problems.GRA with constraints(GRA+)is categorized as a clas...Group role assignment(GRA)is originally a complex problem in role-based collaboration(RBC).The solution to GRA provides modelling techniques for more complex problems.GRA with constraints(GRA+)is categorized as a class of complex assignment problems.At present,there are few generally efficient solutions to this category of problems.Each special problem case requires a specific solution.Group multi-role assignment(GMRA)and GRA with conflicting agents on roles(GRACAR)are two problem cases in GRA+.The contributions of this paper include:1)The formalization of a new problem of GRA+,called group multi-role assignment with conflicting roles and agents(GMAC),which is an extension to the combination of GMRA and GRACAR;2)A practical solution based on an optimization platform;3)A sufficient condition,used in planning,for solving GMAC problems;and 4)A clear presentation of the benefits in avoiding conflicts when dealing with GMAC.The proposed methods are verified by experiments,simulations,proofs and analysis.展开更多
基于角色的协同RBC(Role-Based Collaboration)是一套研究角色及它们之间复杂关系的方法、理论和技术。在RBC中,群组角色分配GRA(Group Role Assignment)既是一个关键问题,也是一个难题。已有许多研究探讨了基于Q(Qualification)矩阵来...基于角色的协同RBC(Role-Based Collaboration)是一套研究角色及它们之间复杂关系的方法、理论和技术。在RBC中,群组角色分配GRA(Group Role Assignment)既是一个关键问题,也是一个难题。已有许多研究探讨了基于Q(Qualification)矩阵来处理GRA问题,但仅利用Q矩阵难以描述问题中的复杂约束关系。因此,将约束集(Constraint)引进E-CARGO模型,提出了带约束的EC-CARGO模型,研究了RBC、GRA、SAT(SATisfaction)和CSP(Constraint Satisfaction Problem)之间的联系,建立了RBC-GRA-SAT-CSP问题求解转换关系;提出应用EC-CARGO模型求解经典CSP约束满足问题的方法,进而描述了应用GRA求解CSP约束满足问题的通用框架。最后以N皇后问题为例,验证了通过GRA的约束指派求解CSP问题的有效性。展开更多
为了解决因孤立时空约束而导致的多项任务指派的协同失效和全局优化性能急剧下降问题,使用角色协同理论(role-based collaboration)及其通用模型E-CARGO的子模型群组角色指派(group role assignment),以机场登机口调度为例,对问题进行...为了解决因孤立时空约束而导致的多项任务指派的协同失效和全局优化性能急剧下降问题,使用角色协同理论(role-based collaboration)及其通用模型E-CARGO的子模型群组角色指派(group role assignment),以机场登机口调度为例,对问题进行指派时空约束形式化建模;分析不同代理承担不同角色、不同代理承担同个角色的协作情况,从而建立量化评估矩阵与协作矩阵;继而对时空约束进行解耦与消解,采用整数规划在追求协作空间利用率最大化的同时,考虑平衡旅客偏好,对问题进行多目标求解。大规模仿真实验论证了模型与方法的一般性、有效性和可靠性。此外,与传统GRA模型相比,主体利益指标提升6.21%,客体偏好指标提升9.72%,实现秒级求解,满足了复杂时空网络下的任务分配快速指派响应要求。展开更多
In reentrant production,decision makers need to consider whether the part should be discarded or reprocessed.It involves the production and time cost that is required by reprocessing.Therefore,an efficient and feasibl...In reentrant production,decision makers need to consider whether the part should be discarded or reprocessed.It involves the production and time cost that is required by reprocessing.Therefore,an efficient and feasible assignment method is required for reentrant production.To tackle this issue,we use the Environments-Classes,Agents,Roles,Groups,and Objects model to formalize this problem.A novel solution is designed for Reentrant Production by extending the Group Role Assignment(GRA)problem model to solve the GRA with Balance problem.With this proposed solution,we can get an allocation scheme that takes into account multi-objective optimization and Pareto equilibrium between average performance of the whole reprocessing system and high defect rate parts.Finally,large-scale simulation experiments based on the Python PuLP platform are carried out to demonstrate the practicability and robustness of the proposed solution.The simulation results provide a solid decision-making reference for the manufacturer.展开更多
基金supported in part by Natural Sciences and Engineering Research Council,Canada(NSERC)(RGPIN-2018-04818)the funding from the Innovation for Defence Excellence and Security(IDEaS)Program from the Canadian Department of National Defence(DND)。
文摘Group role assignment(GRA)is originally a complex problem in role-based collaboration(RBC).The solution to GRA provides modelling techniques for more complex problems.GRA with constraints(GRA+)is categorized as a class of complex assignment problems.At present,there are few generally efficient solutions to this category of problems.Each special problem case requires a specific solution.Group multi-role assignment(GMRA)and GRA with conflicting agents on roles(GRACAR)are two problem cases in GRA+.The contributions of this paper include:1)The formalization of a new problem of GRA+,called group multi-role assignment with conflicting roles and agents(GMAC),which is an extension to the combination of GMRA and GRACAR;2)A practical solution based on an optimization platform;3)A sufficient condition,used in planning,for solving GMAC problems;and 4)A clear presentation of the benefits in avoiding conflicts when dealing with GMAC.The proposed methods are verified by experiments,simulations,proofs and analysis.
文摘为了解决因孤立时空约束而导致的多项任务指派的协同失效和全局优化性能急剧下降问题,使用角色协同理论(role-based collaboration)及其通用模型E-CARGO的子模型群组角色指派(group role assignment),以机场登机口调度为例,对问题进行指派时空约束形式化建模;分析不同代理承担不同角色、不同代理承担同个角色的协作情况,从而建立量化评估矩阵与协作矩阵;继而对时空约束进行解耦与消解,采用整数规划在追求协作空间利用率最大化的同时,考虑平衡旅客偏好,对问题进行多目标求解。大规模仿真实验论证了模型与方法的一般性、有效性和可靠性。此外,与传统GRA模型相比,主体利益指标提升6.21%,客体偏好指标提升9.72%,实现秒级求解,满足了复杂时空网络下的任务分配快速指派响应要求。
基金supported by the National Key Research and Development Program of China No.2022YFB3304400Natural Sciences and Engineering Research Council of Canada(NSERC)under Grant DDG-2024-00036.
文摘In reentrant production,decision makers need to consider whether the part should be discarded or reprocessed.It involves the production and time cost that is required by reprocessing.Therefore,an efficient and feasible assignment method is required for reentrant production.To tackle this issue,we use the Environments-Classes,Agents,Roles,Groups,and Objects model to formalize this problem.A novel solution is designed for Reentrant Production by extending the Group Role Assignment(GRA)problem model to solve the GRA with Balance problem.With this proposed solution,we can get an allocation scheme that takes into account multi-objective optimization and Pareto equilibrium between average performance of the whole reprocessing system and high defect rate parts.Finally,large-scale simulation experiments based on the Python PuLP platform are carried out to demonstrate the practicability and robustness of the proposed solution.The simulation results provide a solid decision-making reference for the manufacturer.
