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Cooperative Co-evolutionary Optimisation on Work Package Scheduling and Staff Assignments

Cooperative Co-evolutionary Optimisation on Work Package Scheduling and Staff Assignments. Jian Ren , Mark Harman CREST Centre, SSE Group, UCL 23 Feb, 2011, 11 th COW. Outline. Research Motivations Solutions Representations: WPO and Staffing Fitness Evaluation: Simulation of Execution

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Cooperative Co-evolutionary Optimisation on Work Package Scheduling and Staff Assignments

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  1. Cooperative Co-evolutionary Optimisation on Work Package Scheduling and Staff Assignments JianRen, Mark Harman CREST Centre, SSE Group, UCL 23 Feb, 2011, 11th COW

  2. Outline Research Motivations Solutions Representations: WPO and Staffing Fitness Evaluation: Simulation of Execution Cooperative Coevolution Process Empirical Results and Issues Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman

  3. Motivations Staff Assignments (Team Construction) How to assign staff into project teams? Work Packages Scheduling (WP Ordering) How to put the WPs in a good order to execute? Objective Find earlier completion time of a project by optimising TC and WPOsimultaneously Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman

  4. Solution Representation of TC N staff Species #1: assignment of staff to teams How to assign N staff into M teams? Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman

  5. Genetic Operator on TC Parent_1 Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman

  6. Genetic Operator on TC Parent_1 Parent_2 Single Point Crossover Child_1 Child_2 Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman

  7. Solution Representation of WPO Species #2: orderings of the WPs How to put the WPs in a perfect or near perfect order? Perfect ordering = All teams are busy all the time and finish their last WP at the same time Solution: Attributes of WP ID Efforts: total efforts required by executing the WP Dependency: ID of its predecessor Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman

  8. Genetic Operator on WPO Parent_1 Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman

  9. Genetic Operator on WPO Parent_1 Parent_2 B: the rest of the other parent after WPs in A are deleted A: copied from one parent Child_1 Child_2 Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman

  10. Fitness Evaluation Processing Simulator The `Best` available team picks the next WP before other available teams. First Come First Served One WP blocks the queue of waiting WPs until its predecessors are all finished. Objective Earlier Overall Completion Time = Higher Fitness Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman

  11. Fitness Evaluation Processing Simulator Objective Earlier Overall Completion Time = Higher Fitness Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman

  12. Fitness Evaluation Processing Simulator Objective Earlier Overall Completion Time = Higher Fitness Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman

  13. Fitness Evaluation Processing Simulator The latest finishing time is the overall completion time of a simulation. Objective Earlier Overall Completion Time = Higher Fitness Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman

  14. Cooperative Coevolutionary Process Initialisation for both species //(S1: TC, S2: WPO) FOR (E = 1 : External_Generations) FOR (I = 1 : Internal_Generations) internal evolutionary progress for Species #1 end FOR FOR (I = 1 : Internal_Generations) internal evolutionary progress for Species #2 end FOR end FOR Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman

  15. Cooperative Co-Evolution Algorithm Internal evolutionary process for TC Evolved TC Evolved WPO Internal evolutionary process for WPO Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman

  16. Coevolutionary Process on Boxplot Internal Generation Num = 10 External Generation Num = 10 X: Generation Num (Time) Y: Project Completion Time

  17. Preliminary Empirical Results Given the same number of evaluation efforts, CCEA finds better solutions than single population EA. Optimisation on WPO contributes more benefit than on TC. Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman

  18. CCEA finds better solutions than single-species EA 3 sets of configurations are applied to 4 real-world projects. Comparing the earliest finishing time found by I, II and III: * Configuration III can be considered as single-species EA, as the FOR loop has only been executed once. No interactions between two population have chance to happy before the end of the FOR loop. It is an extreme case of CCEA. Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman

  19. Optimisation on WPO contributes more benefit than on TC Internal Generation Num = 100 External Generation Num = 1 X: Generation Num (Time) Y: Project Completion Time

  20. Preliminary Empirical Results Given the same number of evaluation efforts, CCEA finds better solutions than single population EA. Optimisation on WPO contributes more benefit than on TC. Different configurations of the CCEA produce results with different characteristics. Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman

  21. Issues & Future Work Cooperative Coevolutionary Optimisation on Work Package Scheduling and Staff Assignments Jian Ren & Mark Harman Problem Model Staffing skills, changing teams during the project, absence, etc WP changed during the project, mis-estimate efforts The configurations of CCEA is complex. Diversity of the species of Team Constructions, Processing Simulator (execution of WPs) Job-shop scheduling permutation, etc Comparison and Validation Single-species EA (Statistics Analysis) Verification by More Real-world Data from Software Project Management, Cloud Computing

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