Multi-choice mixed integer goal programming optimization for real problems in a sugar and ethanol milling company

Applied Mathematical Modelling

Volumn 37, Issue 9, 2013, Pages 6146-6162

  da Silva, Aneirson Francisco ^a   Silva Marins, Fernando Augusto ^a   Barra Montevechi, José Arnaldo ^b  

^a SÃO PAULO STATE UNIVERSITY UNESP   (Brazil)

^b FEDERAL UNIVERSITY OF ITAJUBÁ   (Brazil)

Author keywords

Aggregate production planning; Goal programming; Multi Choice mixed integer goal programming; Multi choice aspiration levels; Sugar and ethanol mills

Indexed keywords

AGGREGATE PRODUCTION PLANNING; ANALYTICAL APPROACH; GOAL PROGRAMMING; GOAL PROGRAMMING MODEL; MULTI CHOICES; MULTIPLE ASPIRATION LEVELS; PRODUCTION PROCESS; REAL-WORLD PROBLEM;

AGGREGATES; ETHANOL; INDUSTRY; INTEGER PROGRAMMING; LOADING; MILLING (MACHINING); PRODUCTION ENGINEERING;

PROBLEM SOLVING;

EID: 84875377451     PISSN: 0307904X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apm.2012.12.022     Document Type: Article

References (54)

1. Salassi M.E., Breaux J.B., Naquim C.J. Modeling within-season sugarcane growth for optimal harvest system. Agric. Syst. 2002, 73:261-278.
2. Conab (National Supply Company): Technical Report. 2010 (accessed 23.04.10). http://www.conab.gov.br/.
3. Colin E. Mathematical programming accelerates implementation of agro-industrial sugarcane complex. Eur. J. Oper. Res. 2009, 199:232-235.
4. Licht F.O. World Ethanol Biofuels Rep. 2010, 8(16):328.
5. United States Department of Agricultures USDA. 2012 (accessed 10.11.12). http://www.moneycontrol.com/news_html_files/broker_report/2011/Feb0511-7050211.pdf.
6. Iannoni A.P., Morabito R.A. Discrete simulation analysis of a logistics supply system. Transp. Res. Part E: Logist. Transp. Rev. 2006, 42:191-210.
7. J.A.B. Montevechi, A.F. de Pinho, L. Fabiano, F.A.S. Marins, Application of design of experiments on the simulation of a process in an automotive industry, in: Proceedings of the Winter Simulation Conference 2007.
8. Kawamura M.S., Ronconi D.P., Yoshizaki H. Optimizing transportation and storage of final products in the sugar and ethanol industry. Int. Trans. Oper. Res. 2006, 13(5):425-439.
9. Mathew J., Rajendran C. Scheduling of maintenance activities in a sugar industry using simulation. Comput. Ind. 1993, 21:331-334.
10. Cock J.H., Luna C.A., Palma A. The trade-off between total harvestable production and concentration of the economically useful yield component: cane tonnage and sugar content. Field Crops Res. 2000, 67:257-262.
11. Higgins A.J., Davies I. A simulation model for capacity planning in sugar cane transport. Comput. Electron. Agric. 2005, 47:85-102.
12. Yoshizaki H.T.Y., Muscat A.R.N., Biazzi J.L. Decentralizing ethanol distribution in southeastern Brazil. Interfaces 1996, 26(6):24-34.
13. Jiuping X., Limming Y. A class of expected value multi-objective programming problems with rough coefficients. Math. Comput. Modell. 2009, 50:141-158.
14. Wey V.M., Wu K.Y. Using ANP priorities with goal programming in resource allocation in transportation. Math. Comput. Modell. 2007, 46:100-985.
15. Higgins A.J. Scheduling of road vehicles in sugar transport: a case study at an Australian sugar mill. Eur. J. Oper. Res. 2006, 170:987-1000.
16. Higgins A.J., Antony G., Davies I., Sandel G., Prestwidge D., Andrew B.A. Framework for integrating a complex harvesting and transport system for sugar production. Agric. Syst. 2004, 82:99-115.
17. Milan E.L., Fernandez S.M., Aragones L.M.P. Sugar cane transportation in Cuba, a case study. Eur. J. Oper. Res. 2006, 174:374-386.
18. Paiva R.P.O., Morabito R. An optimization model for the aggregate production planning of a Brazilian sugar and ethanol milling company. Ann. Oper. Res. 2009, 169:117-130.
19. Bertolini M., Bevilacqua M. A combined goal programming - AHP approach to maintenance selection problem. Reliab. Eng. Syst. Saf. 2006, 91:839-848.
20. Schniederjans M.J., Tim G. Using the analytic hierarchy process and multi-objective programming for the selection of cost drivers in activity-based costing. Eur. J. Oper. Res. 1997, 100:72-80.
21. Gokcen H., Erel E. A goal programming approach to mixed-model assembly line balancing problem. Int. J. Prod. Econ. 1997, 48:177-185.
22. Badri M.A. Combining the analytic hierarchy process and goal programming for global facility location-allocation problem. Int. J. Prod. Econ. 1999, 62:237-248.
23. Wang R.C., Liang T.F. Applying possibilistic linear programming to aggregate production planning. Int. J. Prod. Econ. 2005, 98:328-341.
24. Grunow M., Günter H.O., Westinner R. Supply optimization for the production of raw sugar. Int. J. Prod. Econ. 2007, 110:224-239.
25. Lisson S.N., Inman-Bamber N.G., Robertson M.J., Keating B.A. The historical and future contribution of crop physiology and modelling research to sugarcane production systems. Field Crops Res. 2005, 92:321-335.
26. Leung S.C.H., Chan S.S.W. A goal programming model for aggregate production planning with resource utilization constraint. Comput. Ind. Eng. 2009, 56:138-141.
27. Liao C.N. Formulating the multi-segment goal programming. Comput. Ind. Eng. 2009, 56:1053-1064.
28. Chang C.-T. Multi-choice goal programming. Int. J. Manage. Sci. 2007, 35:389-396.
29. Ignizio J.P. Goal Programming and Extensions 1976, Lexington Books, Lexington, MA.
30. Chang C.-T. Revised multi-choice goal programming. Appl. Math. Modell. 2008, 32:2587-2595.
31. Chang C.T., Lin T.C. Interval goal programming for S-shaped penalty function. Eur. J. Oper. Res. 2009, 199:9-20.
32. Chang C.-T. Revised multi-choice goal programming for multi-period, multi-stage inventory controlled supply chain model with popup stores in Guerrilla marketing. Appl. Math. Modell. 2010, 58:3586-3598.
33. Chang C.-T., Chen H.-M., Zhuang Z.-Y. Revised multi-segment goal programming: percentage goal programming. Comput. Ind. Eng. 2012, 63:1235-1242.
34. Chang C.-T., Chen H.-M., Zhuang Z.-Y. Multi-coefficients goal programming. Comput. Ind. Eng. 2012, 62:616-623.
35. Deb K. Multi-Objective Optimization using Evolutionary Algorithms 2001, John Wiley & Sons.
36. Ackoff R.L. Resurrecting the future of operational research. J. Oper. Res. Soc. 1979, 30:189-199.
37. Tamiz M., Jones D., El-Darzi E. A review of goal programming and its applications. Ann. Oper. Res. 1995, 58:39-53.
38. Tamiz M., Jones D.F., Romero C. Goal programming for decision making: an overview of the current state-of-the-art. Eur. J. Oper. Res. 1998, 111:569-581.
39. Cohon J.L. Multiobjective Programming and Planning 2005, Dover.
40. Charnes A., Cooper W.W. Management Model and Industrial Application of Linear Programming 1961, vol. 1. Wiley, New York.
41. Jones D.F., Tamiz M. Expanding the flexibility of goal programming via preference modelling techniques. Int. J. Manage. Sci. 1995, 23:41-48.
42. Biswas A., Pal B.B. Application of fuzzy goal programming technique to land use planning in agricultural system. Int. J. Manage. Sci. 2005, 33:391-398.
43. Pati R.K., Vrat P., Kumar P. A goal programming model for paper recycling system. Int. J. Manage. Sci. 2008, 36:405-417.
44. Linares P., Romero C. Aggregation of preferences in an environmental economics context: a goal-programming approach. Int. J. Manage. Sci. 2002, 30:89-95.
45. Romero C. A general structure of achievement function for a goal programming model. Eur. J. Oper. Res. 2004, 153:675-686.
46. Aouni B., Kettani O. Goal programming model: a glorious history and a promising future. Eur. J. Oper. Res. 2001, 133:225-231.
47. Uri{dotless}́a M.V.R., Caballero R., Ruiz F., Romero C. Meta-goal programming. Eur. J. Oper. Res. 2002, 136:422-429.
48. R. Caballero, T. Gómez, F. Ruiz, Goal programming: realistic targets for the near future, J. Multi-Criteria Decis. Anal. (2009). doi:10.1002/mcda.442.
49. Bertrand J.W.M., Fransoo J.C. Operations management research methodologies using quantitative modeling. Int. J. Oper. Prod. Manage. 2002, 22:241-264.
50. Bryman A., Bell E. Business Research Methods 2007, Oxford University Press. second ed.
51. Wu D.D., Zhang Y., Wu D., Olson D.L. Fuzzy multi-objective programming for supplier selection and risk modeling: a possibility approach. Eur. J. Oper. Res. 2010, 200:774-787.
52. Aouni B., Martel J.M., Hassaine A. Fuzzy goal programming model: an overview of the current state-of-the Art. Microelectron. Reliab. 2009, 33:63-80.
53. Bankian-Tabrizi B., Shahanaghi K., Jabalameli M.S. Fuzzy multi-choice goal programming. Appl. Math. Modell. 2012, 36:1415-1420.
54. Kazemzadeh R.B., Bashiri M., Atkinson A.C., Noorossana R. A general framework for multiresponse optimization problems based on goal programming. Eur. J. Oper. Res. 2008, 189:421-429.