Multi-objective human resources allocation in R&D projects planning

In a R&D department, several projects may have to be implemented simultaneously within a certain period of time by a limited number of human resources with diverse skills. This paper proposes an optimisation model for the allocation of multi-skilled human resources to R&D projects, considering individual workers as entities having different knowledge, experience and ability. The model focuses on three fundamental aspects of human resources: the different skill levels, the learning process and the social relationships existing in working teams. The resolution approach for the multi-objective problem consists of two steps: firstly, a set of non-dominated solutions is obtained by exploring the optimal Pareto frontier and secondly, based on further information, the ELECTRE III method is utilised to select the best compromise with regards to the considered objectives. The uncertainty associated to each solution is modelled by fuzzy numbers and used in establishing the threshold values of ELECTRE III, while the weights of the objectives are determined taking into account the influence that each objective has on the others.

[1]  Thomas L. Saaty,et al.  Decision making with dependence and feedback : the analytic network process : the organization and prioritization of complexity , 1996 .

[2]  M. Bohanec,et al.  The Analytic Hierarchy Process , 2004 .

[3]  L. Lasdon,et al.  On a bicriterion formation of the problems of integrated system identification and system optimization , 1971 .

[4]  Masataka Yoshimura,et al.  Decision-making support system for human resource allocation in product development projects , 2006 .

[5]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[6]  Shigeo Kawata,et al.  Workers' placement in an industrial environment , 1999, Fuzzy Sets Syst..

[7]  W. Pedrycz Why triangular membership functions , 1994 .

[8]  Matt Bassett Assigning projects to optimize the utilization of employees' time and expertise , 2000 .

[9]  S French,et al.  Multicriteria Methodology for Decision Aiding , 1996 .

[10]  Carl T. Haas,et al.  Assignment and Allocation Optimization of Partially Multiskilled Workforce , 2002 .

[11]  T. L. Saaty,et al.  Decision making with dependence and feedback , 2001 .

[12]  Gwo-Hshiung Tzeng,et al.  Multi-criteria task assignment in workflow management systems , 2003, 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the.

[13]  Kalyanmoy Deb,et al.  Multi-objective optimization using evolutionary algorithms , 2001, Wiley-Interscience series in systems and optimization.

[14]  Muh-Cherng Wu,et al.  A project scheduling and staff assignment model considering learning effect , 2006 .

[15]  D A Nembhard,et al.  Heuristic approach for assigning workers to tasks based on individual learning rates , 2001 .