Complementing Solutions to Optimization Problems via Crowdsourcing on Video Game Plays

Applied Sciences

Huaxing Zhu¹  DianaA. Leon-Velasco²  JoséEmmanuel Ramirez-Marquez³  Chi Zhang⁴  Raúl Monroy⁵  Mariano Vargas-Santiago⁵ 

[1] Department of Industrial Engineering, Tsinghua University, Beijing 100084, China;Department of Mathematics, Universidad Autónoma Metropolitana, Cuajimalpa 05348, Mexico;Enterprise Science and Engineering Division, Stevens Institute of Technology, School of Systems & Enterprises, Hoboken, NJ 07030, USA;School of Economics and Engineering, Beijing University of Technology, Beijing 100124, China;Tecnologico de Monterrey, School of Engineering and Science, Carretera al Lago de Guadalupe Km. 3.5, Atizapán, Estado de Mexico 52926, Mexico;

关键词: combinatorial optimization;    facilities planning and design;    multiple objective programming;    genetic algorithms;    scheduling;   

DOI  :  10.3390/app10238410

来源: DOAJ

【 摘 要 】

Leveraging human insight and intuition has been identified as having the potential for the improvement of traditional algorithmic methods. For example, in a video game, a user may not only be entertained but may also be challenged to beat the score of another player; additionally, the user can learn complicated concepts, such as multi-objective optimization, with two or more conflicting objectives. Traditional methods, including Tabu search and genetic algorithms, require substantial computational time and resources to find solutions to multi-objective optimization problems (MOPs). In this paper, we report on the use of video games as a way to gather novel solutions to optimization problems. We hypothesize that humans may find solutions that complement those found mechanically either because the computer algorithm did not find a solution or because the solution provided by the crowdsourcing of video games approach is better. We model two different video games (one for the facility location problem and one for scheduling problems), we demonstrate that the solution space obtained by a computer algorithm can be extended or improved by crowdsourcing novel solutions found by humans playing a video game.

【 授权许可】

Unknown