TY - GEN
T1 - The Performance of a Metaheuristic Algorithm for Finding a Maximal Weight Clique in the Fill-in-Blank Problem
AU - Kanahara, Kazuho
AU - Katayama, Kengo
AU - Funabiki, Nobuo
AU - Tomita, Etsuji
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/3/28
Y1 - 2020/3/28
N2 - A programming education is one of the most important fields in Information and Education Technology. Funabiki et al. have developed a Web-based Java Programming Learning Assistant System (JPLAS). JPLAS mainly provides two types of problems, namely the code writing problem and the fill-in-blank problem, to support students' self-studies at various learning levels. Particularly in the fill-in-blank problem (FIBP), the system requires an efficient algorithm to find a maximal clique of the compatibility graph in advance in order to obtain a maximal set of blank elements with unique answers. In this paper, we investigate the performance of a metaheuristic algorithm based on an iterated local search for solving the maximum weight clique problem (MWCP), which is an important generalization of the maximum clique problem, given as an extension of the compatibility graph in the FIBP. Computational results show that our metaheuristic algorithm is capable of finding satisfactory weighted cliques efficiently for well-known benchmark graphs and the performance of our algorithm is comparable to those of state-of-the-art metaheuristics for the MWCP.
AB - A programming education is one of the most important fields in Information and Education Technology. Funabiki et al. have developed a Web-based Java Programming Learning Assistant System (JPLAS). JPLAS mainly provides two types of problems, namely the code writing problem and the fill-in-blank problem, to support students' self-studies at various learning levels. Particularly in the fill-in-blank problem (FIBP), the system requires an efficient algorithm to find a maximal clique of the compatibility graph in advance in order to obtain a maximal set of blank elements with unique answers. In this paper, we investigate the performance of a metaheuristic algorithm based on an iterated local search for solving the maximum weight clique problem (MWCP), which is an important generalization of the maximum clique problem, given as an extension of the compatibility graph in the FIBP. Computational results show that our metaheuristic algorithm is capable of finding satisfactory weighted cliques efficiently for well-known benchmark graphs and the performance of our algorithm is comparable to those of state-of-the-art metaheuristics for the MWCP.
KW - Combinatorial Optimization
KW - Fill-in-Blank Problem
KW - Java Programming Education
KW - Local Search
KW - Maximal Weight Clique Problem
KW - Metaheuristic
UR - http://www.scopus.com/inward/record.url?scp=85085944549&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85085944549&partnerID=8YFLogxK
U2 - 10.1145/3395245.3396407
DO - 10.1145/3395245.3396407
M3 - Conference contribution
AN - SCOPUS:85085944549
T3 - ACM International Conference Proceeding Series
SP - 257
EP - 261
BT - Proceedings of the 2020 8th International Conference on Information and Education Technology, ICIET 2020
PB - Association for Computing Machinery
T2 - 8th International Conference on Information and Education Technology, ICIET 2020
Y2 - 28 March 2020 through 30 March 2020
ER -