Simulation modelling and multi-layer genetic algorithms to identify optimal crew allocation in the precast industry

Research output: Contribution to conference › Paper › peer-review

Abstract

This paper presents an innovative approach to solve complex crew allocation problems in any labour-intensive industry.

The full text is available from: http://www.engineering.nottingham.ac.uk/icccbe/proceedings/html/197.htm

@conference{e56c27d44ed74b0797788783d4ed273f,

title = "Simulation modelling and multi-layer genetic algorithms to identify optimal crew allocation in the precast industry",

abstract = "This paper presents an innovative approach to solve complex crew allocation problems in any labour-intensive industry.",

keywords = "simulation, genetic algorithms, precast concrete, allocation problem",

author = "Ammar Al-Bazi and N. Dawood",

note = "The full text is available from: http://www.engineering.nottingham.ac.uk/icccbe/proceedings/html/197.htm",

year = "2010",

language = "English",

pages = "393",

}

TY - CONF

T1 - Simulation modelling and multi-layer genetic algorithms to identify optimal crew allocation in the precast industry

AU - Al-Bazi, Ammar

AU - Dawood, N.

N1 - The full text is available from: http://www.engineering.nottingham.ac.uk/icccbe/proceedings/html/197.htm

PY - 2010

Y1 - 2010

N2 - This paper presents an innovative approach to solve complex crew allocation problems in any labour-intensive industry.

AB - This paper presents an innovative approach to solve complex crew allocation problems in any labour-intensive industry.

KW - simulation

KW - genetic algorithms

KW - precast concrete

KW - allocation problem

M3 - Paper

SP - 393

ER -