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An integrated dynamic facility layout and job shop scheduling problem: A hybrid NSGA-II and local search algorithm
Determining personnel promotion policies in HEI
1. | Department of Management / ETSEIB. Universitat Politcnica de Catalunya, Av. Diagonal 647, 7th floor, Barcelona, 08028, Spain |
2. | Department of Management / IOC / ETSEIB. Universitat Politcnica de Catalunya, Av. Diagonal 647, 11th floor, Barcelona, 08028, Spain |
3. | Department of Management / IOC / ETSEIB. Universitat Politcnica de Catalunya, Av. Diagonal 647, 7th floor, Barcelona, 08028, Spain |
4. | Department of Industrial Management. Ghent University, Technologiepark 902, 9052 Zwijnaarde, Belgium |
This paper addresses the determination of personnel promotion policies in public Higher Education Institutions (HEI) considering aspects such as worker's promotion rules, hiring and laying off, workforce diversity and budget constraints. The problem is formulated as a Mixed Integer Linear Program. The objective of the proposed optimization model is not only expressed in economic terms but also addressing the achievement of a preferable staff composition and service level. The model is formulated generally, hence it can be useful for different types of universities taken into account their specificities and characteristics. Specifically, this paper addresses the problem of finding the relationship between economic resources for workers'promotion and the pursued preferable staff composition. The model is applied to a real case, in which several analyses are performed under different scenarios characterized by possible trends in the available budget and the demand. The analyses are for different workforce structures, which reflect different academic and personnel policies. The results address the performance of the proposed model in achieving the preferable structure and also on how promotions --and associated expenditures--, are for young researchers and experienced personnel according to each considered scenario.
References:
[1] |
T. Agasisti, M. Arnaboldi and G. Azzone,
Strategic management accounting in universities: The Italian experience, Higher Education, 55 (2008), 1-15.
doi: 10.1007/s10734-006-9032-6. |
[2] |
G. Agiomirgianakis, D. Serenis and N. Tsounis,
A distance learning university and its economic impact in a country's peripheries: The case of Hellenic Open University, Operational Research, 17 (2017), 165-186.
doi: 10.1007/s12351-015-0220-y. |
[3] |
H. S. Ahn, R. Righter and J. G. Shanthikumar,
Staffing decisions for heterogeneous workers with turnover, Mathematical Methods of Operations Research, 62 (2005), 499-514.
doi: 10.1007/s00186-005-0033-5. |
[4] |
R. Birnbaum,
The life cycle of academic management fads, Journal of Higher Education, 71 (2000), 1-16.
doi: 10.2307/2649279. |
[5] |
B. R. Clark,
Sustaining change in universities: Continuities in case studies and concepts, Tertiary Education and Management, 9 (2003), 99-116.
doi: 10.1080/13583883.2003.9967096. |
[6] |
A. Corominas, R. Pastor and E. Rodríguez,
Rotational allocation of tasks to multifunctional workers in a service industry, International Journal of Production Economics, 103 (2005), 3-9.
doi: 10.1016/j.ijpe.2005.05.015. |
[7] |
A. Corominas, A. Lusa and J. Olivella,
A detailed workforce planning model including non-linear dependence of capacity on the size of the staff and cash management, European Journal of Operational Research, 216 (2012), 445-458.
doi: 10.1016/j.ejor.2011.06.027. |
[8] |
J. J. da Cunha Jr and M. C. de Souza, A linearized model for academic staff assignment in a Brazilian university focusing on performance gain in quality indicators, International Journal of Production Economics, 197 (2018), 43-51. Google Scholar |
[9] |
R. de la Torre, A. Lusa and M. Mateo, A MILP Model for the Long Term Academic Staff Size and Composition Planning in Public Universities, Omega, 63 (2016), 1-11. Google Scholar |
[10] |
R. de la Torre, A. Lusa and M. Mateo,
Evaluation of the impact of strategic staff planning in a university using a MILP model, European Journal of Industrial Engineering, 11 (2017), 328-352.
doi: 10.1504/EJIE.2017.084879. |
[11] |
L. Elwood and A. Rainnie, Strategic planning in Ireland's Institutes of Technology, Higher Education Policy, 23 (2012), 107-129. Google Scholar |
[12] |
A. T. Ernst, H. Jiang, M. Krishnamoorthy and D. Sier,
Staff scheduling and rostering: A review of applications, methods and models, European Journal of Operational Research, 153 (2004), 3-27.
doi: 10.1016/S0377-2217(03)00095-X. |
[13] |
C. Heimerl and R. Kolisch,
Scheduling and staffing multiple projects with a multi-skilled workforce, OR Spectrum, 32 (2010), 343-368.
doi: 10.1007/s00291-009-0169-4. |
[14] |
W. H. Hu, M. S. Lavieri, A. Toriello and X. Liu,
Strategic health workforce planning, IIE Transaction, 48 (2016), 1127-1138.
doi: 10.1080/0740817X.2016.1204488. |
[15] |
M. L. Jorge, J. H. Madueno and F. J. A Pena, Factors influencing the presence of sustainability initiatives in the strategic planning of Spanish universities, Environmental Education Research, 21 (2015), 1155-1187. Google Scholar |
[16] |
S. Kim and D. Nembhard,
Cross-trained staffing level with heterogeneous learning/forgetting, IEEE Transactions of Engineering Management, 57 (2010), 560-574.
doi: 10.1109/TEM.2010.2048905. |
[17] |
P. M. Koeleman, S. Bhulai and M. van Meersbergen,
Optimal patient and personnel scheduling policies for care-at-home service facilities, European Journal of Operational Research, 219 (2012), 557-563.
doi: 10.1016/j.ejor.2011.10.046. |
[18] |
D. Lillis, Steering by Engagement: Towards an Integrated Planning and Evaluation Framework in Higher Education Institutes, European forum for quality assurance: Embedding quality culture in higher education, Dublin, 2006. Google Scholar |
[19] |
X. Llinàs-Audet, M. Girotto and F. Solé, University strategic management and the efficacy of the managerial tools: The case of the Spanish universities, Revista de Educación, 355 (2011), 33-54. Google Scholar |
[20] |
M. Lounsbury, Institutional sources of practice variation: Staffing College and university recycling programs, Administrative Science Quarterly, 46 (2001), 29-56. Google Scholar |
[21] |
J. A. D. Machuca, M. M. González-Zamora and V. G. Aguilar-Escobar,
Service operations management research, Journal of Operations Management, 25 (2007), 585-603.
doi: 10.1016/j.jom.2006.04.005. |
[22] |
B. Maenhout and M. Vanhoucke,
An integrated nurse staffing and scheduling analysis for longer-term nursing staff allocation problems, Omega, 41 (2013), 485-499.
doi: 10.1016/j.omega.2012.01.002. |
[23] |
C. Martínez-Costa, M. Mas-Machuca, E. Benedito and A. Corominas, A review of mathematical programming models for strategic capacity planning in manufacturing, International Journal of Production Economics, 153 (2014), 65-85. Google Scholar |
[24] |
M. Mckelvet and M. Holmen, Learning to Compete in European Universities: From Social Institution to Knowledge Business, Edward Elgar Publishing Limited, Cheltenham, 2009. Google Scholar |
[25] |
A. V. Roth and L. J. Menor,
Insights into service operations management: A research agenda, Production and Operations Management, 12 (2003), 145-164.
doi: 10.1111/j.1937-5956.2003.tb00498.x. |
[26] |
G. Sharrock,
Four management agendas for Australian universities, Journal of Higher Education Policy and Management, 34 (2012), 323-337.
doi: 10.1080/1360080X.2012.678728. |
[27] | M. Shattock, Managing Successful Universities, Society for Research in Higher Education & Open University Press, London, 2003. Google Scholar |
[28] |
L. Simeone, G. Secundo and G. Schiuma,
Adopting a design approach to translate needs and interests of stakeholders in academic entrepreneurship: The MIT Senseable City Lab case, Technovation, 64/65 (2017), 58-67.
doi: 10.1016/j.technovation.2016.12.001. |
[29] |
H. Song and H. C. Huang,
A successive convex approximation method for multistage workforce capacity planning problem with turnover, European Journal of Operational Research, 188 (2008), 29-48.
doi: 10.1016/j.ejor.2007.04.018. |
[30] |
R. Subbaye and R. Vithal,
Teaching criteria that matter in university academic promotions, Assessment & Evaluation in Higher Education, 42 (2016), 37-60.
doi: 10.1080/02602938.2015.1082533. |
[31] |
I. Ugboro, K. Obeng and O. Spam,
Strategic planning as an effective tool of strategic management in public sector organizations: evidence from public transit organizations, Administration & Society, 43 (2011), 87-123.
doi: 10.1177/0095399710386315. |
[32] |
G. Willis, C. Siôn and M. Kunc,
Strategic workforce planning in healthcare: A multi-methodology approach, European Journal of Production Research, 267 (2018), 250-263.
doi: 10.1016/j.ejor.2017.11.008. |
[33] |
M. Würmseher, To each his own: Matching different entrepreneurial models to the academic scientist's individual needs, Technovation, 59 (2017), 1-17. Google Scholar |
show all references
References:
[1] |
T. Agasisti, M. Arnaboldi and G. Azzone,
Strategic management accounting in universities: The Italian experience, Higher Education, 55 (2008), 1-15.
doi: 10.1007/s10734-006-9032-6. |
[2] |
G. Agiomirgianakis, D. Serenis and N. Tsounis,
A distance learning university and its economic impact in a country's peripheries: The case of Hellenic Open University, Operational Research, 17 (2017), 165-186.
doi: 10.1007/s12351-015-0220-y. |
[3] |
H. S. Ahn, R. Righter and J. G. Shanthikumar,
Staffing decisions for heterogeneous workers with turnover, Mathematical Methods of Operations Research, 62 (2005), 499-514.
doi: 10.1007/s00186-005-0033-5. |
[4] |
R. Birnbaum,
The life cycle of academic management fads, Journal of Higher Education, 71 (2000), 1-16.
doi: 10.2307/2649279. |
[5] |
B. R. Clark,
Sustaining change in universities: Continuities in case studies and concepts, Tertiary Education and Management, 9 (2003), 99-116.
doi: 10.1080/13583883.2003.9967096. |
[6] |
A. Corominas, R. Pastor and E. Rodríguez,
Rotational allocation of tasks to multifunctional workers in a service industry, International Journal of Production Economics, 103 (2005), 3-9.
doi: 10.1016/j.ijpe.2005.05.015. |
[7] |
A. Corominas, A. Lusa and J. Olivella,
A detailed workforce planning model including non-linear dependence of capacity on the size of the staff and cash management, European Journal of Operational Research, 216 (2012), 445-458.
doi: 10.1016/j.ejor.2011.06.027. |
[8] |
J. J. da Cunha Jr and M. C. de Souza, A linearized model for academic staff assignment in a Brazilian university focusing on performance gain in quality indicators, International Journal of Production Economics, 197 (2018), 43-51. Google Scholar |
[9] |
R. de la Torre, A. Lusa and M. Mateo, A MILP Model for the Long Term Academic Staff Size and Composition Planning in Public Universities, Omega, 63 (2016), 1-11. Google Scholar |
[10] |
R. de la Torre, A. Lusa and M. Mateo,
Evaluation of the impact of strategic staff planning in a university using a MILP model, European Journal of Industrial Engineering, 11 (2017), 328-352.
doi: 10.1504/EJIE.2017.084879. |
[11] |
L. Elwood and A. Rainnie, Strategic planning in Ireland's Institutes of Technology, Higher Education Policy, 23 (2012), 107-129. Google Scholar |
[12] |
A. T. Ernst, H. Jiang, M. Krishnamoorthy and D. Sier,
Staff scheduling and rostering: A review of applications, methods and models, European Journal of Operational Research, 153 (2004), 3-27.
doi: 10.1016/S0377-2217(03)00095-X. |
[13] |
C. Heimerl and R. Kolisch,
Scheduling and staffing multiple projects with a multi-skilled workforce, OR Spectrum, 32 (2010), 343-368.
doi: 10.1007/s00291-009-0169-4. |
[14] |
W. H. Hu, M. S. Lavieri, A. Toriello and X. Liu,
Strategic health workforce planning, IIE Transaction, 48 (2016), 1127-1138.
doi: 10.1080/0740817X.2016.1204488. |
[15] |
M. L. Jorge, J. H. Madueno and F. J. A Pena, Factors influencing the presence of sustainability initiatives in the strategic planning of Spanish universities, Environmental Education Research, 21 (2015), 1155-1187. Google Scholar |
[16] |
S. Kim and D. Nembhard,
Cross-trained staffing level with heterogeneous learning/forgetting, IEEE Transactions of Engineering Management, 57 (2010), 560-574.
doi: 10.1109/TEM.2010.2048905. |
[17] |
P. M. Koeleman, S. Bhulai and M. van Meersbergen,
Optimal patient and personnel scheduling policies for care-at-home service facilities, European Journal of Operational Research, 219 (2012), 557-563.
doi: 10.1016/j.ejor.2011.10.046. |
[18] |
D. Lillis, Steering by Engagement: Towards an Integrated Planning and Evaluation Framework in Higher Education Institutes, European forum for quality assurance: Embedding quality culture in higher education, Dublin, 2006. Google Scholar |
[19] |
X. Llinàs-Audet, M. Girotto and F. Solé, University strategic management and the efficacy of the managerial tools: The case of the Spanish universities, Revista de Educación, 355 (2011), 33-54. Google Scholar |
[20] |
M. Lounsbury, Institutional sources of practice variation: Staffing College and university recycling programs, Administrative Science Quarterly, 46 (2001), 29-56. Google Scholar |
[21] |
J. A. D. Machuca, M. M. González-Zamora and V. G. Aguilar-Escobar,
Service operations management research, Journal of Operations Management, 25 (2007), 585-603.
doi: 10.1016/j.jom.2006.04.005. |
[22] |
B. Maenhout and M. Vanhoucke,
An integrated nurse staffing and scheduling analysis for longer-term nursing staff allocation problems, Omega, 41 (2013), 485-499.
doi: 10.1016/j.omega.2012.01.002. |
[23] |
C. Martínez-Costa, M. Mas-Machuca, E. Benedito and A. Corominas, A review of mathematical programming models for strategic capacity planning in manufacturing, International Journal of Production Economics, 153 (2014), 65-85. Google Scholar |
[24] |
M. Mckelvet and M. Holmen, Learning to Compete in European Universities: From Social Institution to Knowledge Business, Edward Elgar Publishing Limited, Cheltenham, 2009. Google Scholar |
[25] |
A. V. Roth and L. J. Menor,
Insights into service operations management: A research agenda, Production and Operations Management, 12 (2003), 145-164.
doi: 10.1111/j.1937-5956.2003.tb00498.x. |
[26] |
G. Sharrock,
Four management agendas for Australian universities, Journal of Higher Education Policy and Management, 34 (2012), 323-337.
doi: 10.1080/1360080X.2012.678728. |
[27] | M. Shattock, Managing Successful Universities, Society for Research in Higher Education & Open University Press, London, 2003. Google Scholar |
[28] |
L. Simeone, G. Secundo and G. Schiuma,
Adopting a design approach to translate needs and interests of stakeholders in academic entrepreneurship: The MIT Senseable City Lab case, Technovation, 64/65 (2017), 58-67.
doi: 10.1016/j.technovation.2016.12.001. |
[29] |
H. Song and H. C. Huang,
A successive convex approximation method for multistage workforce capacity planning problem with turnover, European Journal of Operational Research, 188 (2008), 29-48.
doi: 10.1016/j.ejor.2007.04.018. |
[30] |
R. Subbaye and R. Vithal,
Teaching criteria that matter in university academic promotions, Assessment & Evaluation in Higher Education, 42 (2016), 37-60.
doi: 10.1080/02602938.2015.1082533. |
[31] |
I. Ugboro, K. Obeng and O. Spam,
Strategic planning as an effective tool of strategic management in public sector organizations: evidence from public transit organizations, Administration & Society, 43 (2011), 87-123.
doi: 10.1177/0095399710386315. |
[32] |
G. Willis, C. Siôn and M. Kunc,
Strategic workforce planning in healthcare: A multi-methodology approach, European Journal of Production Research, 267 (2018), 250-263.
doi: 10.1016/j.ejor.2017.11.008. |
[33] |
M. Würmseher, To each his own: Matching different entrepreneurial models to the academic scientist's individual needs, Technovation, 59 (2017), 1-17. Google Scholar |











Category group | Description of workers | Tasks |
Full Professor (highest categories within KC and KP groups of categories) | This category is composed by the most skilled and experienced workers. Workers within these categories can perform some managerial tasks in the HEI governor (i.e. dean of the faculty). | ⅰ) Lead projects / processes, ⅱ) Conduct research, ⅲ) Provide strategic vision for projects in research and technology transfer, as well as for the strategic objectⅳes for the department, ⅳ) Publish scientific results from research, ⅴ) Teach professionals in lower categories, ⅶ) Develop management tasks |
Tenured Assistant Professor (within KC group of categories) and Tenured Professor (within KP group of categories). | This group of categories is composed by high experienced workers in all aspects of teaching and research. Workers have also skills in scientific project leading. | ⅰ) Lead projects / processes, ⅱ) Conduct research, ⅲ) Publish scientific results from research, ⅳ) Teach professionals in lower categories. |
Tenure-track Lecturer (within KT group of categories). | This group of categories is composed by professionals with high capacity for carrying out teaching and research actⅳities, with more expertise and knowledge than those in the categories under KT | ⅰ) Collaborate in the management of projects and processes, ⅱ) Execute projects required high degree of specialization, ⅲ) Supervise research, ⅳ) Publish scientific results from research, ⅴ) Teach young researchers and pupils. |
Assistant Lecturer (within KT group of categories) | This group of categories is composed by workers starting their career; thus, they are still in training processes for teaching and research purposes. | ⅰ) Participate in research and technology transfer projects, ⅱ) Execute projects under the advice of colleagues in upper categories, ⅲ) Support teaching actⅳities. |
Category group | Description of workers | Tasks |
Full Professor (highest categories within KC and KP groups of categories) | This category is composed by the most skilled and experienced workers. Workers within these categories can perform some managerial tasks in the HEI governor (i.e. dean of the faculty). | ⅰ) Lead projects / processes, ⅱ) Conduct research, ⅲ) Provide strategic vision for projects in research and technology transfer, as well as for the strategic objectⅳes for the department, ⅳ) Publish scientific results from research, ⅴ) Teach professionals in lower categories, ⅶ) Develop management tasks |
Tenured Assistant Professor (within KC group of categories) and Tenured Professor (within KP group of categories). | This group of categories is composed by high experienced workers in all aspects of teaching and research. Workers have also skills in scientific project leading. | ⅰ) Lead projects / processes, ⅱ) Conduct research, ⅲ) Publish scientific results from research, ⅳ) Teach professionals in lower categories. |
Tenure-track Lecturer (within KT group of categories). | This group of categories is composed by professionals with high capacity for carrying out teaching and research actⅳities, with more expertise and knowledge than those in the categories under KT | ⅰ) Collaborate in the management of projects and processes, ⅱ) Execute projects required high degree of specialization, ⅲ) Supervise research, ⅳ) Publish scientific results from research, ⅴ) Teach young researchers and pupils. |
Assistant Lecturer (within KT group of categories) | This group of categories is composed by workers starting their career; thus, they are still in training processes for teaching and research purposes. | ⅰ) Participate in research and technology transfer projects, ⅱ) Execute projects under the advice of colleagues in upper categories, ⅲ) Support teaching actⅳities. |
Model A | Model B | Model C | |
Proportion of workers in | 42% | 34% | 27% |
Proportion of workers in | 17% | 18% | 16% |
Proportion of workers in | 41% | 48% | 57% |
Model A | Model B | Model C | |
Proportion of workers in | 42% | 34% | 27% |
Proportion of workers in | 17% | 18% | 16% |
Proportion of workers in | 41% | 48% | 57% |
Sc. | Initial comp. | Pref. comp. | Dem.-Budget | Sc. | Initial comp. | Pref. comp. | Dem.-Budget | Sc. | Initial comp. | Pref. comp. | Dem.-Budget |
1 | A | A | CC | 22 | A | B | CC | 43 | A | C | CC |
2 | A | A | CD | 23 | A | B | CD | 44 | A | C | CD |
3 | A | A | DC | 24 | A | B | DC | 45 | A | C | DC |
4 | A | A | DD | 25 | A | B | DD | 46 | A | C | DD |
5 | A | A | IC | 26 | A | B | IC | 47 | A | C | IC |
6 | A | A | II | 27 | A | B | II | 48 | A | C | II |
7 | A | A | ID | 28 | A | B | ID | 49 | A | C | ID |
8 | B | A | CC | 29 | B | B | CC | 50 | B | C | CC |
9 | B | A | CD | 30 | B | B | CD | 51 | B | C | CD |
10 | B | A | DC | 31 | B | B | DC | 52 | B | C | DC |
11 | B | A | DD | 32 | B | B | DD | 53 | B | C | DD |
12 | B | A | IC | 33 | B | B | IC | 54 | B | C | IC |
13 | B | A | II | 34 | B | B | II | 55 | B | C | II |
14 | B | A | ID | 35 | B | B | ID | 56 | B | C | ID |
15 | C | A | CC | 36 | C | B | CC | 57 | C | C | CC |
16 | C | A | CD | 37 | C | B | CD | 58 | C | C | CD |
17 | C | A | DC | 38 | C | B | DC | 59 | C | C | DC |
18 | C | A | DD | 39 | C | B | DD | 60 | C | C | DD |
19 | C | A | IC | 40 | C | B | IC | 61 | C | C | IC |
20 | C | A | II | 41 | C | B | II | 62 | C | C | II |
21 | C | A | ID | 42 | C | B | ID | 63 | C | C | ID |
Sc. | Initial comp. | Pref. comp. | Dem.-Budget | Sc. | Initial comp. | Pref. comp. | Dem.-Budget | Sc. | Initial comp. | Pref. comp. | Dem.-Budget |
1 | A | A | CC | 22 | A | B | CC | 43 | A | C | CC |
2 | A | A | CD | 23 | A | B | CD | 44 | A | C | CD |
3 | A | A | DC | 24 | A | B | DC | 45 | A | C | DC |
4 | A | A | DD | 25 | A | B | DD | 46 | A | C | DD |
5 | A | A | IC | 26 | A | B | IC | 47 | A | C | IC |
6 | A | A | II | 27 | A | B | II | 48 | A | C | II |
7 | A | A | ID | 28 | A | B | ID | 49 | A | C | ID |
8 | B | A | CC | 29 | B | B | CC | 50 | B | C | CC |
9 | B | A | CD | 30 | B | B | CD | 51 | B | C | CD |
10 | B | A | DC | 31 | B | B | DC | 52 | B | C | DC |
11 | B | A | DD | 32 | B | B | DD | 53 | B | C | DD |
12 | B | A | IC | 33 | B | B | IC | 54 | B | C | IC |
13 | B | A | II | 34 | B | B | II | 55 | B | C | II |
14 | B | A | ID | 35 | B | B | ID | 56 | B | C | ID |
15 | C | A | CC | 36 | C | B | CC | 57 | C | C | CC |
16 | C | A | CD | 37 | C | B | CD | 58 | C | C | CD |
17 | C | A | DC | 38 | C | B | DC | 59 | C | C | DC |
18 | C | A | DD | 39 | C | B | DD | 60 | C | C | DD |
19 | C | A | IC | 40 | C | B | IC | 61 | C | C | IC |
20 | C | A | II | 41 | C | B | II | 62 | C | C | II |
21 | C | A | ID | 42 | C | B | ID | 63 | C | C | ID |
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