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Financial planning using goal programming

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  • Kvanli, Alan H

Abstract

Financial planners within industrial organizations are often given the impossible task of formulating a multi-year financial plan which is severely over-constrained. As the planner attempts to meet one objective another variable (or ratio of variables) becomes unacceptable and he is faced with the familiar 'balloon squeezing' effect. The problem is one of multiple conflicting objectives (goals) hence lends itself very well to a goal programming method of solution. This approach provides a powerful 'what-if' device for the financial planner and allows him to arrive at a satisfactory solution by examining the various trade-offs among the conflicting goals. To be an effective and usable tool, the individual goals are not assigned a priority coefficient as is typical of most goal programming applications. Rather, the planner can reflect his priorities in the manner in which he performs the subsequent what-if analyses. Also, a more flexible penalty function is introduced allowing the planner to assign a more realistic set of penalities which vary in severity over a specified range. Methods of implementing this concept are discussed which overcome the problems created by the immense storage requirements and the necessity of assigning the various penalties.

Suggested Citation

  • Kvanli, Alan H, 1980. "Financial planning using goal programming," Omega, Elsevier, vol. 8(2), pages 207-218.
  • Handle: RePEc:eee:jomega:v:8:y:1980:i:2:p:207-218
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    Citations

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    Cited by:

    1. Hamalainen, Raimo P. & Mantysaari, Juha, 2002. "Dynamic multi-objective heating optimization," European Journal of Operational Research, Elsevier, vol. 142(1), pages 1-15, October.
    2. M. Ortuño & B. Vitoriano, 2011. "A goal programming approach for farm planning with resources dimensionality," Annals of Operations Research, Springer, vol. 190(1), pages 181-199, October.
    3. Tamiz, Mehrdad & Jones, Dylan & Romero, Carlos, 1998. "Goal programming for decision making: An overview of the current state-of-the-art," European Journal of Operational Research, Elsevier, vol. 111(3), pages 569-581, December.
    4. Cinzia Colapinto & Raja Jayaraman & Simone Marsiglio, 2017. "Multi-criteria decision analysis with goal programming in engineering, management and social sciences: a state-of-the art review," Annals of Operations Research, Springer, vol. 251(1), pages 7-40, April.
    5. Chang, Ching-Ter & Lin, Teng-Chiao, 2009. "Interval goal programming for S-shaped penalty function," European Journal of Operational Research, Elsevier, vol. 199(1), pages 9-20, November.
    6. Bertolini, Massimo & Bevilacqua, Maurizio, 2006. "A combined goal programming—AHP approach to maintenance selection problem," Reliability Engineering and System Safety, Elsevier, vol. 91(7), pages 839-848.
    7. Pal, Bijay Baran & Nath Moitra, Bhola, 2003. "A goal programming procedure for solving problems with multiple fuzzy goals using dynamic programming," European Journal of Operational Research, Elsevier, vol. 144(3), pages 480-491, February.
    8. Chen, Liang-Hsuan & Tsai, Feng-Chou, 2001. "Fuzzy goal programming with different importance and priorities," European Journal of Operational Research, Elsevier, vol. 133(3), pages 548-556, September.
    9. Aouni, Belaid & Colapinto, Cinzia & La Torre, Davide, 2014. "Financial portfolio management through the goal programming model: Current state-of-the-art," European Journal of Operational Research, Elsevier, vol. 234(2), pages 536-545.
    10. Cherif, Mohamed Sadok & Chabchoub, Habib & Aouni, Belaid, 2008. "Quality control system design through the goal programming model and the satisfaction functions," European Journal of Operational Research, Elsevier, vol. 186(3), pages 1084-1098, May.
    11. Tom Rihm & Philipp Baumann, 2018. "Staff assignment with lexicographically ordered acceptance levels," Journal of Scheduling, Springer, vol. 21(2), pages 167-189, April.

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