Greedy algorithms for the profit-aware social team formation problem

2021 ◽  
Author(s):  
Shengxin Liu ◽  
Chung Keung Poon
Keyword(s):  
Greedy Algorithms ◽  
Team Formation ◽  
Formation Problem

Project Team Formation Based on Knowledge and Cooperation Degree

2010 ◽  
Vol 44-47 ◽  
pp. 3143-3147
Author(s):  
Xiao Rong Huang ◽  
Shun Sheng Guo ◽  
Li Bo Sun
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Calculation Method ◽  
Project Team ◽  
Team Formation ◽  
Individual Member ◽  
Formation Model ◽  
Collaborative Model ◽  
Team Members ◽  
Formation Problem

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.

scholarly journals An improved Jaya algorithm with a modified swap operator for solving team formation problem

2020 ◽  
Vol 24 (21) ◽  
pp. 16627-16641
Author(s):  
Walaa H. El-Ashmawi ◽  
Ahmed F. Ali ◽  
Adam Slowik
Keyword(s):  
Optimization Algorithm ◽  
Heuristic Algorithms ◽  
Single Point ◽  
Real Life ◽  
Team Formation ◽  
Jaya Algorithm ◽  
African Buffalo ◽  
Team Members ◽  
Formation Problem ◽  
Swap Operator

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.

scholarly journals Finding Optimal Team for Multiskill Task Based on Vehicle Sensors Data

2017 ◽  
Vol 2017 ◽  
pp. 1-10
Author(s):  
Bowen Du ◽  
Qian Tao ◽  
Feng Zhu ◽  
Tianshu Song
Keyword(s):  
Software Development ◽  
Spatial Data ◽  
Spatial Information ◽  
Greedy Algorithms ◽  
Team Formation ◽  
Spatial Crowdsourcing ◽  
Multiple Phase ◽  
Individual Variations ◽  
Effectiveness And Efficiency ◽  
Vehicle Sensors

These days, with the increasingly widespread employment of sensors, particularly those attached to vehicles, the collection of spatial data is becoming easier and more accurate. As a result, many relevant areas, such as spatial crowdsourcing, are gaining ever more attention. A typical spatial crowdsourcing scenario involves an employer publishing a task and some workers helping to accomplish it. However, most of previous studies have only considered the spatial information of workers and tasks, while ignoring individual variations among workers. In this paper, we consider the Software Development Team Formation (SDTF) problem, which aims to assemble a team of workers whose abilities satisfy the requirements of the task. After showing that the problem is NP-hard, we propose three greedy algorithms and a multiple-phase algorithm to approximately solve the problem. Extensive experiments are conducted on synthetic and real datasets, and the results verify the effectiveness and efficiency of our algorithms.

scholarly journals Optimization of Harmony in Team Formation Problem for Sports Clubs: A Real-Life Volleyball Team Application

2018 ◽  
Vol 8 (2) ◽  
Author(s):  
Gerçek Budak ◽  
İmdat Kara ◽  
Yusuf Tansel İç ◽  
Refail Kasımbeyli
Keyword(s):  
Real Life ◽  
Team Formation ◽  
Sports Clubs ◽  
Formation Problem
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