Ementa

Modelagem Matemática para Tomada de Decisão

Nível: Mestrado Profissional
Obrigatória: Não
Carga Horária: 48
Créditos: 4.0

Ementa

Proporcionar ao corpo discente entendimento sobre o processo de modelagem matemática para a tomada de decisão empresarial. Desenvolver conhecimentos de modelos envolvendo o emprego de regras estatísticas e matemáticas, visando a tomada de decisão com base nos resultados gerados (saídas). Os temas a serem desenvolvidos são: Elementos de matemática (notação, funções e relações lineares); Programação linear (PL); Programação linear Inteira (PLI); Programação Linear por Metas.

Referências:

Abdeljaouad, M. A. et al. Job-shop production scheduling with reverse flows. European Journal of Operational Research, v.244, p.117-128, 2015.

Abedi, A.; Zhu, W. An optimisation model for purchase, production and distribution in fish supply chain – a case study. International Journal of Production Research, v.55, n.12, p.3451-3464, 2017.

Agra, A.; Sousa, A.; Doostmohammadi, M. The Minimum Cost Design of Transparent Optical Networks Combining Grooming, Routing, and Wavelength Assignment. IEEE/ACM Transactions on Networking, v.24, n.6, p.3702-3713, 2016.

Amin, S.; Tamima, U.; Amador-Jiménez, L.E. Optimal pavement management: Resilient roads in support of emergency response of cyclone affected coastal areas. Transportation Research Part A, v.119, p.45-61, 2019.

Aroui, K.; Alpan, G.; Frein, Y. Minimising work overload in mixed-model assembly lines with different types of operators: a case study from the truck industry. International Journal of Production Research, v.55, n.21, p.6305-6326, 2017.

Bertrand, A. et al. Regional waste heat valorisation: A mixed integer linear programming method for energy service companies. Energy, v.167, p.454-468, 2019.

Brandinu, G.;Trautmann, N. A mixed-integer linear programming approach to the optimization of event-bus schedules: a scheduling application in the tourism sector. Journal of Scheduling, v.17, n.6, p.621-629, 2014.

Carter, M.; Price, C. C.; Rabadi, G. Operations Research: A Practical Introduction. Londres (GB): Chapman and Hall/CRC, 2018.

Chou, F. N.-F.; Wu, C.-W. Determination of cost coefficients of a priority-based water allocation linear programming model - a network flow approach. Hydrology and Earth System Sciences, v.18, n.5, p.1857-1872, 2014.

Costa, A.; Fichera, A. A mixed-integer linear programming (MILP) model for the evaluation of CHP system in the context of hospital structures. Applied Thermal Engineering, v.71, n.2, p.921-929, 2014.

Detienne, B. A mixed integer linear programming approach to minimize the number of late jobs with and without machine availability constraints. European Journal of Operational Research, v.235, n.3, p.540-552, 2014.

Fang, C. et al. Optimal production planning in a hybrid manufacturing and recovering system based on the internet of things with closed loop supply chains. Operational Research, v.16, n.3, p.543-577, 2016.

Fooks, J. R.; Messer, K. D.; Kecinski, M. A Cautionary Note on the Use of Benefit Metrics for Cost-Effective Conservation. Environmental and Resource Economics, v.71, n.4, p.985-999, 2018.

Gross, C. N.; Fügener, A.; Brunner, J. O. Online rescheduling of physicians in hospitals. Flexible Services and Manufacturing Journal, v.30, p.296-328, 2018.

Hossain, S. J.; Sarker, B. R. Optimal locations of on-line and off-line rework stations in a serial production system. International Journal of Production Research, v.54, n.12, p.3603–3621, 2016.

Ishak, S. A.; Hashim, H.; Ting, T. S. Eco innovation strategies for promoting cleaner cement manufacturing. Journal of Cleaner Production, v.136, p. 133-149, 2016.

Kreter, S. et al. Mixed-integer linear programming and constraint programming formulations for solving resource availability cost problems. European Journal of Operation Research, v.266, p.472-486, 2018.

Larrosa, A. P. Q.; Cadaval, T. R. S.; Pinto, L. A. A. Influence of drying methods on the characteristics of a vegetable paste formulated by linear programming maximizing antioxidant activity. LWT- Food Science and Technology, v.60, n.1, p.178-185, 2015.

Levesque, S.; Delisle, H.; Agueh, V. Contribution to the development of a food guide in Benin: linear programming for the optimization of local diets. Public Health Nutrition, v.18, n.4, p.622-631, 2015.

Martinsen, G. et al. Joint optimization of water allocation and water quality management in Haihe River basin. Science of the Total Environment, v.654, p.72-84, 2019.

Moghaddam, E. E.; Beyranvand, H.; Salehi, J. A. Routing, Spectrum and Modulation Level Assignment, and Scheduling in Survivable Elastic Optical Networks Supporting Multi-Class Traffic. Journal of Lightwave Technology, v.36, n.23, p.5451-5461, 2018.

Muis et al. Sustainable multi-period electricity planning for Iskandar Malaysia. Clean Technologies and Environmental Policy, v.18, n.8, p. 2467-2478, 2016.

Paulo, W. L.; Fernandes, F. C.; Zanievicz, M. Optimization model of financial resources for business risk management. Systems & Management, v.12, n.1. p.98-107, 2017.

Peng, T.; Zhou, B. Scheduling multiple servers to facilitate just-in-time part-supply in automobile assembly lines. Assembly Automation, v.38, n.3, p.347-360, 2018.

Quezada, E. L.; Lopez-Ospina, H. A. A method for designing a strategy map using AHP and linear programming. International Journal of Production Economics, v.158, p.244-255, 2014.

Ragsdale, C. Spreadsheet Modeling & Decision Analysis: A Practical Introduction to Business Analytics. 8. ed. Boston: Cengage Learning, 2017.

Rostami, B. et al. Reliable single allocation hub location problem under hub breakdowns. Computers and Operations Research, v.96, p.15-29, 2018.

Veselovska, I. L. A Linear programming model of integrating flexibility measures into production processes with cost minimization. Journal of Small Business and Entrepreneurship Development, v.2, n.1, p.67-82, 2014.

Wallerand, A. S. et al. Optimal design of solar-assisted industrial processes considering heat pumping: Case study of a dairy. Renewable Energy, v.128, p.565-585, 2018.

Zarbakhshnia, N. et al. A novel multi-objective model for green forward and reverse logistics network design. Journal of Cleaner Production, v.208, p.1304-1316, 2019.