The International Journal of Advanced Manufacturing Technology

, Volume 65, Issue 1, pp 183-196

First online:

Multi-objective stochastic programming to solve manpower allocation problem

  • Mostafa EkhtiariAffiliated withDepartment of Industrial & Mechanical Engineering, Islamic Azad University, Qazvin Branch Email author 
  • , Keivan GhoseiriAffiliated withDepartment of Civil and Environmental Engineering, University of Maryland

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Effective manpower allocation is among the most vital and complicated decisions for most companies on account of imprecise nature of input information of the problem. This paper presents a novel combination of the chance-constrained programming and the global criterion model for manpower allocation problem that is called chance-constrained global criterion. The proposed model is a deterministic equivalent for the multi-objective stochastic problem of manpower allocation. To illustrate the model, a tri-objective stochastic manpower allocation case problem for determining optimal number of manpower in a job-shop manufacturing system is formulated and solved, and then the competitive advantages of the model are discussed. To have a better judgment on the validity and performance efficiency of the model, 20 different problems are generated and solved. The results show that increasing the size of problem do not have much effect on the number of iterations required for finding the optimal solution, and this model decreases complicacy in modeling the problem.


Chance-constrained programming approach Global criterion Multi-objective stochastic programming Manpower allocation problem