Space-Time Repetitive Project Scheduling Considering Location and Congestion

Construction time optimization is affected greatly by the negotiation between owners and contractors, whose progress is dictated by their desire to maximize system revenues. This paper builds an agent-based model and designs an experimental scenario in which the contractor has competitive and social welfare preferences relevant to the Chinese context; we subdivide competitive preference into greed and jealousy components and subdivide social welfare preference into generosity and sympathy components. We analyze the impacts of these different contractor preferences on the revenue-sharing coefficient, negotiation success rate, and negotiation time when negotiation reaches agreement. The results show that the jealousy component of competitive preference has an important influence on improving the income of the subject, while the greed component does not significantly enhance the revenue-sharing coefficient. The sympathy component of social welfare preference does not have an influence on the revenue-sharing coefficient no matter the strength of the generosity component. Increasing the greed component of competitive preference will lead to the extension of negotiation time and, to a certain extent, to the reduction of the negotiation success rate; the sympathy component of social welfare preference does not have an influence on negotiation time no matter the strength of the generosity preference.

Section: Introductionmentioning

confidence: 99%

Negotiation for Time Optimization in Construction Projects with Competitive and Social Welfare Preferences

Meng

et al. 2019

“…Therefore, the subject's behavior and decision making will show diverse characteristics. For different scenarios in the project construction phase, such as schedule control [69], cost control, operating environment conditions, and policy environment, the adaptability of the subject's behavior may lead to different behaviors, resulting in multiple manifestations of unsafe behavior [70], like incorrectly using safety protection supplies, violating the regulations, and paying little attention to protecting oneself and other people.…”

Section: Author Indicatorsmentioning

confidence: 99%

Analysis of Complexity of Unsafe Behavior in Construction Teams and a Multiagent Simulation

Zhu

et al. 2018

Self Cite

The processes in construction are more likely than others to breed unsafe behaviors, and the consequences of these actions can be serious. This paper first reviews the research status on unsafe behavior in construction teams. It then analyzes the complex mechanisms that lead to unsafe behavior and constructs a three-layer structural model based on agent-based modeling (ABM) technology. This modeling deals with complexity and elaborates on key points and potential research ideas in the study of unsafe behavior in construction teams. Using the ABM method, the effects of different incentive strategies on the safe behavior of construction teams under different management scenarios were studied. The results showed that when members have a fair perception of the situation, the effect of the excess performance reward distribution, according to the member's safety awareness level, is better than the average distribution effect. This is the case whether the member's safety behavior level is positively or negatively related to the member's safety awareness level. This study proves the feasibility, validity, and universality of the three-layer structural model. It also reaches certain management conclusions and ideas for further development. The purpose of this paper is to provide a reference for research on the containment and prevention of unsafe behavior in construction teams.

“…where the constraints given by (18) and (19) define the feasible region S ∈ ℝ n and the vector of decision variables x = x 1 , x 2 , … , x n belongs to S. The above objective values involve k conflicting functions f i ℝ n → ℝ that we want to minimize simultaneously.…”

Section: M2 Minmentioning

confidence: 99%

“…Afshar-Nadjafi [17] investigated the multimode project scheduling problem under the condition of decision making of recruitment and release for resources. Tao et al [18] investigated coupling project scheduling and resource flow allocation in repetitive projects considering site location and workspace congestion. Dong et al [19] took the feature of flexible resource renting and leasing into project scheduling problem.…”

Section: Construction Scheduling and Resource Allocationmentioning

confidence: 99%

Robust Optimization for Integrated Construction Scheduling and Multiscale Resource Allocation

Tao

Chong

et al. 2018

Self Cite

This research investigates an integrated problem of construction scheduling and resource allocation. Inspired by complex construction practices, multi-time scale resources are considered for different length of terms, such as permanent staff and temporary workers. Differing from the common stochastic optimization problems, the resource price is supposed to be an uncertain parameter of which probability distribution is unknown, but observed data is given. Hence, the problem here is called Data-Driven Construction Scheduling and Multiscale Resource Allocation Problem (DD-CS&MRAP). Based on likelihood robust optimization, a multiobjective programming is developed where project completion time and expected resource cost are minimized simultaneously. To solve the problem efficiently, a double-layer metaheuristic comprised of Multiple Objective Particle Swarm Optimization (MOPSO) and interior point method named MOPSO-interior point algorithm is designed. The new solution presentation scheme and decoding process are developed. Finally, a construction case is used to validate the proposed method. The experimental results indicate that the MOPSO-interior point algorithm can reduce resource cost and improve the efficiency of resource utilization.