A win–win team formation problem based on the negotiation

2015 ◽  
Vol 44 ◽  
pp. 137-152 ◽  
Author(s):  
Jian Wang ◽  
Jia Zhang
2010 ◽  
Vol 44-47 ◽  
pp. 3143-3147
Author(s):  
Xiao Rong Huang ◽  
Shun Sheng Guo ◽  
Li Bo Sun

To aim at the project team formation problem, this study proposes a formation model based on knowledge and cooperation degree. The ability of individual member and cooperation degree of team members are considered. In addition ,it presents a way of measuring candidate’s ability about knowledge, and establishes a collaborative model to measure the cooperation degree between team members. Furthermore, a calculation method of knowledge and cooperation degree is proposed, and then a mathematical model is established. Finally it presented a solution base on Genetic Algorithm for this model.


2020 ◽  
Vol 24 (21) ◽  
pp. 16627-16641
Author(s):  
Walaa H. El-Ashmawi ◽  
Ahmed F. Ali ◽  
Adam Slowik

Abstract Forming a team of experts that can match the requirements of a collaborative task is an important aspect, especially in project development. In this paper, we propose an improved Jaya optimization algorithm for minimizing the communication cost among team experts to solve team formation problem. The proposed algorithm is called an improved Jaya algorithm with a modified swap operator (IJMSO). We invoke a single-point crossover in the Jaya algorithm to accelerate the search, and we apply a new swap operator within Jaya algorithm to verify the consistency of the capabilities and the required skills to carry out the task. We investigate the IJMSO algorithm by implementing it on two real-life datasets (i.e., digital bibliographic library project and StackExchange) to evaluate the accuracy and efficiency of proposed algorithm against other meta-heuristic algorithms such as genetic algorithm, particle swarm optimization, African buffalo optimization algorithm and standard Jaya algorithm. Experimental results suggest that the proposed algorithm achieves significant improvement in finding effective teams with minimum communication costs among team members for achieving the goal.


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