TY - JOUR
T1 - Fuzzy Linear and Repetitive Scheduling for Construction Projects
AU - Katsuragawa, Clara Mariana
AU - Lucko, Gunnar
AU - Isaac, Shabtai
AU - Su, Yi
N1 - Funding Information:
The first author gratefully acknowledges Coordenação de Aperfei-çoamento de Pessoal de Nível Superior (Coordination for the Improvement of Higher Education Personnel—CAPES Foundation), Ministry of Education, Brazil, for the 2015 Brazil Scientific Mobility Program.
Funding Information:
1Brazil Scientific Mobility Program 2015 Recipient, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES Foundation), Ministry of Education, Brasília-DF CEP 70.040-020, Brazil; formerly, Undergraduate Research Assistant, Dept. of Civil and Environment Engineering, Catholic Univ. of America, Washington, DC 20064. Email: clara .katsuragawa@gmail.com 2Professor, Dept. of Civil and Environmental Engineering, Catholic Univ. of America, Washington, DC 20064 (corresponding author). ORCID: https://orcid.org/0000-0002-7355-3365. Email: lucko@cua.edu 3Senior Lecturer, Dept. of Structural Engineering, Ben-Gurion Univ. of the Negev, Beersheba 8410501, Israel. Email: isaacsh@bgu.ac.il 4Lecturer, School of Urban Economics and Management, Beijing Univ. of Civil Engineering and Architecture, Beijing 100044, China. Email: suy@bucea.edu.cn Note. This manuscript was submitted on April 23, 2020; approved on September 23, 2020; published online on January 4, 2021. Discussion period open until June 4, 2021; separate discussions must be submitted for individual papers. This paper is part of the Journal of Construction Engineering and Management, © ASCE, ISSN 0733-9364.
Publisher Copyright:
© 2021 American Society of Civil Engineers.
PY - 2021/3/1
Y1 - 2021/3/1
N2 - Unavoidable risks that cause uncertainty within activity durations should be modeled to gain realism in scheduling. While approaches exist for one-dimensional network schedules, two-dimensional linear and repetitive schedules that track both work and time lack such a method. Fuzzy logic can express variability by modeling optimistic, realistic, and pessimistic cases, which, in this study, form a cone of expected activity durations. Previous studies attempted to apply it to linear and repetitive schedules but suffered from inconsistencies that rendered their results incorrect. Therefore, this research proposes a new fuzzy scheduling method. Its contribution is threefold. First, it models linear or segmental activities as continuous yet flexible fuzzy cones. Second, it explicitly expresses continuous buffers in both the time and work/space dimensions to compose an efficient schedule from such inputs. Third, it identifies their full or partial fuzzy criticality and fuzzy float so that managers can split their attention accordingly. It is illustrated by a validation example, which also explains prior inconsistencies. The industry thus gains a new method that considers uncertainty to generate stable and efficient schedules.
AB - Unavoidable risks that cause uncertainty within activity durations should be modeled to gain realism in scheduling. While approaches exist for one-dimensional network schedules, two-dimensional linear and repetitive schedules that track both work and time lack such a method. Fuzzy logic can express variability by modeling optimistic, realistic, and pessimistic cases, which, in this study, form a cone of expected activity durations. Previous studies attempted to apply it to linear and repetitive schedules but suffered from inconsistencies that rendered their results incorrect. Therefore, this research proposes a new fuzzy scheduling method. Its contribution is threefold. First, it models linear or segmental activities as continuous yet flexible fuzzy cones. Second, it explicitly expresses continuous buffers in both the time and work/space dimensions to compose an efficient schedule from such inputs. Third, it identifies their full or partial fuzzy criticality and fuzzy float so that managers can split their attention accordingly. It is illustrated by a validation example, which also explains prior inconsistencies. The industry thus gains a new method that considers uncertainty to generate stable and efficient schedules.
UR - http://www.scopus.com/inward/record.url?scp=85099081056&partnerID=8YFLogxK
U2 - 10.1061/(ASCE)CO.1943-7862.0001996
DO - 10.1061/(ASCE)CO.1943-7862.0001996
M3 - Article
AN - SCOPUS:85099081056
VL - 147
JO - Journal of Construction Engineering and Management - ASCE
JF - Journal of Construction Engineering and Management - ASCE
SN - 0733-9364
IS - 3
M1 - 04021002
ER -