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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 222))

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Introduction

This chapter continues Chapters 7 and 8. However now we have multiple objective functions we wish to maximize. We first discuss the general multiobjective fully fuzzified linear program in the next section. Then we study an example problem in Section 9.3. We have previously obtained an approximate fuzzy solution to this type of problem using an evolutionary algorithm [2]. In Section 9.4 we will apply our fuzzy Monte Carlo method to the problem to generate another approximate solution. Unfortunately, we will be unable to compare our Monte Carlo solution to our previous solution because we now are forced to use a different method of evaluating fuzzy inequalities.

Fuzzy multiobjective linear programming has also (along with fuzzy linear programming) become a large area of research. A few recent references to this topic are the papers ([1],[3],[6],[7],[9],[10],[16],[17]) and books (or articles in these books) ([4],[5],[8],[11]-[15]).

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References

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Buckley, J.J., Jowers, L.J. (2007). Fuzzy Multiobjective LP. In: Monte Carlo Methods in Fuzzy Optimization. Studies in Fuzziness and Soft Computing, vol 222. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76290-4_9

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  • DOI: https://doi.org/10.1007/978-3-540-76290-4_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-76289-8

  • Online ISBN: 978-3-540-76290-4

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