Study On Multi-resource Leveling Optimization Of Engineering Project Based On Resource Scheduling Fee

Resource leveling optimization is a very important issue in project management,which research how to achieve a balanced use of resources under the total duration existed.It is difficult to solve optimization model belonging to NP-hard problem theoretically.Resource leveling optimization has been the research forefront of project management for dozens years and has achieves fruitful results.In the construction process,the ups and downs phenomenon of resource consumption often leads to increase labor slowdown,idle equipment or add temporary facilities.It will result in unnecessary waste and affect the level of project benefits,and therefore,the resource leveling consumption is very important.In this context,multi-resource leveling optimization problem is researched from the perspective of resource scheduling fee based on previous studies.It will avoid three questions: the importance of resources determination;non-dimensional treatment of resource demand;the correlation between resources.The resource scheduling fee is defined as additional costs in order to ensure the normal work of resource at a specific place and time.The resource scheduling fee includes human resource scheduling fee(acquisition costs,development costs,slowdown compensation,termination costs,opening costs),materials scheduling fee(procurement costs,storage charges,opening costs),equipment scheduling fee(slotting and exiting fee,demolition charges,slowdown compensation).The multi-resource leveling optimization model is built using resource scheduling fee lowest as evaluation index and is solved with genetic algorithm by MATLAB toolbox.The optimal case is gotten that the actual start time of A,B,C,D,E,F,G,H and F work is 0,0,0,2,4,7,6,6,12.In this case,a total resource scheduling fee of 6720 yuan happens,and 1130 yuan has been saved,14.39% of total resource scheduling fee.This study demonstrated the resource scheduling fee as objective function is reasonable and accurate,but also provides a new way of thinking to solve the multi-project resource leveling optimization.