.png){kind=icon}
.png){kind=icon}
Return
Simulation-Based Auction Protocol for Resource Scheduling Problems
.png){kind=icon}
PRE
AI
DOI：10.1061/(ASCE)CO.1943-7862.0000399.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Resource scheduling, or the allocation of resources over time, is a challenging problem in large-scale or multiple-project environments. Traditional network scheduling techniques are ineffective in modeling the dynamic nature and resource interactions of large or multiunit projects. This paper presents a simulation-based auction protocol (SBAP) to solve resource scheduling problems in large-scale construction projects. SBAP is a hybrid framework that integrates multi agent resource allocation (MARA) in a simulation environment. SBAP deploys a centralized resource allocation approach, referred to as an auction protocol, whereby agents bid on different combinations of resources at the start of a simulation cycle. Agents attempt to improve their individual welfare by acquiring a combination of resources; an auctioneer looks at the entire system and allocates resources to the agents using a combinatorial algorithm to maximize an overall objective function (e.g., maximizing the system's revenue or minimizing total costs). The auction is repeated on a regular basis. Simulation is also employed in large-scale projects to track the availability of resources, capture and release the resources, and satisfy constraints of the problem. This paper demonstrates the architecture of the SBAP framework and discusses implementation of SBAP in a real case study of crane allocation in an industrial project. DOI: 10.1061/(ASCE)CO.1943-7862.0000399. (C) 2012 American Society of Civil Engineers.
Keywords:
Resource scheduling
Simulation
Multiagent
Auction protocol
Combinatorial algorithms
Crane allocation
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
J
IF:
5.1
Papers:
5.1K
Citations:
1.4W