Solving the Many to Many Grouped Task Allocation Problem via E-CARGO

EasyChair Preprint 11148

Abstract

The task allocation between team members of each organization's departments is a crucial project management activity that needs adequate attention to improve organizational efficiency. If a related decision is not made properly, it may immediately cause problems with coordination and communication, task delays, and increased costs. Tasks are usually grouped and then these groups are assigned to the agents. Moreover, it is important to consider the difficulty level of the tasks and the member’s ability. The task allocation process becomes increasingly complex when administrators strive to maintain the balance between the workload of allocated task groups and the agents' capabilities. The E-CARGO (Environments - Classes, Agents, Roles, Groups, and Objects) model, created for the purpose of Role-Based Collaboration (RBC), has been effectively utilized to address the given problem. In this paper, a novel approach is presented to formalize the Grouped Task Allocation Problem (GTAP) employing an extended Group Multirole Assignment with Conflicting Roles problem (GMRACR), which is a sub-model of E-CARGO. In this paper, a role negotiation method is introduced, which is based on GMRACR. It employs a partitioning clustering algorithm along with the Analytic Hierarchy Process (AHP) to evaluate the difficulty level of tasks and the abilities of agents, respectively. This formalization of GTAP facilitates the identification of a solution using the IBM ILOG CPLEX optimization package (CPLEX). The proposed method helps decision-makers with a framework to successfully assign balanced grouped tasks. Through simulation experiments on a real-world problem, the efficacy of the suggested approach is substantiated. Experimental results reveal the practicality of the solutions recommended in this paper.

Keyphrases: Group Multirole Assignment with conflicting roles(GMRACR), Grouped task allocation, IBM ILOG CPLEX optimization (CPLEX) package, Partitioning clustering method, Role-Based Collaboration (RBC)

@booklet{EasyChair:11148,
  author    = {Mozhdeh Noroozi Rasoolabadi and Haibin Zhu and Chun Wang},
  title     = {Solving the Many to Many Grouped Task Allocation Problem via E-CARGO},
  howpublished = {EasyChair Preprint 11148},
  year      = {EasyChair, 2023}}