SOLVING FUZZY LINEAR PROGRAMMING PROBLEM USING SUPPORT AND CORE OF FUZZY NUMBERS

Similar documents
Simplex Method for Fuzzy Variable Linear Programming Problems

Simplex Method for Solving Linear Programming Problems with Fuzzy Numbers

LU FACTORIZATION. ELM1222 Numerical Analysis. ELM1222 Numerical Analysis Dr Muharrem Mercimek

[ 20 ] 1. Inequality exists only between two real numbers (not complex numbers). 2. If a be any real number then one and only one of there hold.

CHAPTER 2 FUZZY NUMBER AND FUZZY ARITHMETIC

Krein's method and mixed integral equation of Volterra Fredholm type. R. T. Matoog

Solving Fuzzy Linear Fractional Programming Problem using LU Decomposition Method

Numerical Solution of Fuzzy Fredholm Integral Equations of the Second Kind using Bernstein Polynomials

A Constructive Proof of Fundamental Theory for Fuzzy Variable Linear Programming Problems

OSCILLATORY AND NON OSCILLATORY PROPERTIES OF RICCATI TYPE DIFFERENCE EQUATIONS

MA123, Chapter 9: Computing some integrals (pp )

Infinite Series Sequences: terms nth term Listing Terms of a Sequence 2 n recursively defined n+1 Pattern Recognition for Sequences Ex:

MATH 174: Numerical Analysis. Lecturer: Jomar F. Rabajante 1 st Sem AY

Schrödinger Equation Via Laplace-Beltrami Operator

Chapter Real Numbers

INTEGRAL SOLUTIONS OF THE TERNARY CUBIC EQUATION

POWER SERIES R. E. SHOWALTER

Linear Programming. Preliminaries

Introduction. Question: Why do we need new forms of parametric curves? Answer: Those parametric curves discussed are not very geometric.

M.Jayalakshmi and P. Pandian Department of Mathematics, School of Advanced Sciences, VIT University, Vellore-14, India.

10.5 Power Series. In this section, we are going to start talking about power series. A power series is a series of the form

Approximate Integration

Numbers (Part I) -- Solutions

Fuzzy Shortest Path with α- Cuts

Numerical Solutions of Fredholm Integral Equations Using Bernstein Polynomials

Discrete Mathematics I Tutorial 12

f(bx) dx = f dx = dx l dx f(0) log b x a + l log b a 2ɛ log b a.

The Elementary Arithmetic Operators of Continued Fraction

ICS141: Discrete Mathematics for Computer Science I

CHAPTER 5d. SIMULTANEOUS LINEAR EQUATIONS

On Distance and Similarity Measures of Intuitionistic Fuzzy Multi Set

Lesson-2 PROGRESSIONS AND SERIES

A Graph Model Proposal for Convex Non Linear Separable Problems with Linear Constraints

SM2H. Unit 2 Polynomials, Exponents, Radicals & Complex Numbers Notes. 3.1 Number Theory

Isolating the Polynomial Roots with all Zeros Real

MA6351 TRANSFORMS AND PARTIAL DIFFERENTIAL EQUATIONS L T P C

CALCULATION OF CONVOLUTION PRODUCTS OF PIECEWISE DEFINED FUNCTIONS AND SOME APPLICATIONS

{ } { S n } is monotonically decreasing if Sn

Section 6.3: Geometric Sequences

Content: Essential Calculus, Early Transcendentals, James Stewart, 2007 Chapter 1: Functions and Limits., in a set B.

Statistics for Financial Engineering Session 1: Linear Algebra Review March 18 th, 2006

degree non-homogeneous Diophantine equation in six unknowns represented by x y 2z

We will begin by supplying the proof to (a).

MTH 146 Class 16 Notes

Double Sums of Binomial Coefficients

1. Introduction. ) only ( See theorem

MATH 104 FINAL SOLUTIONS. 1. (2 points each) Mark each of the following as True or False. No justification is required. y n = x 1 + x x n n

Some New Iterative Methods Based on Composite Trapezoidal Rule for Solving Nonlinear Equations

Some Results of Intuitionistic Fuzzy Soft Matrix Theory

: : 8.2. Test About a Population Mean. STT 351 Hypotheses Testing Case I: A Normal Population with Known. - null hypothesis states 0

Unit 1. Extending the Number System. 2 Jordan School District

Review of Sections

On The Homogeneous Quintic Equation with Five Unknowns

Taylor series expansion of nonlinear integrodifferential equations

APPLICATION OF DIFFERENCE EQUATIONS TO CERTAIN TRIDIAGONAL MATRICES

( a n ) converges or diverges.

MAGIC058 & MATH64062: Partial Differential Equations 1

Power Series Solutions to Generalized Abel Integral Equations

Fuzzy Erlangian Queuing System with State Dependent Service Rate, Balking, Reneging and Retention of Reneged customers

THE CONSERVATIVE DIFFERENCE SCHEME FOR THE GENERALIZED ROSENAU-KDV EQUATION

lecture 16: Introduction to Least Squares Approximation

Vectors. Vectors in Plane ( 2

( ) = A n + B ( ) + Bn

Variational Iteration Method for Solving Volterra and Fredholm Integral Equations of the Second Kind

UNIVERSITY OF CALICUT SCHOOL OF DISTANCE EDUCATION. (2014 Admn. onwards) III Semester. B.Sc. Mathematics CORE COURSE CALCULUS AND ANALYTICAL GEOMETRY

Introduction to Digital Signal Processing(DSP)

BULLETIN OF MATHEMATICS AND STATISTICS RESEARCH

INTEGRATION TECHNIQUES (TRIG, LOG, EXP FUNCTIONS)

Avd. Matematisk statistik

Math 124B January 24, 2012

n 2 + 3n + 1 4n = n2 + 3n + 1 n n 2 = n + 1

PROGRESSIONS AND SERIES

Convergence rates of approximate sums of Riemann integrals

Chapter 7 Infinite Series

3.1 Laplace s Equation 3.2 The Method of Images 3.3 Separation of Variables

An Intuitionistic fuzzy count and cardinality of Intuitionistic fuzzy sets

MAT2400 Assignment 2 - Solutions

Laws of Integral Indices

If a is any non zero real or imaginary number and m is the positive integer, then a...

Fundamentals of Mathematics. Pascal s Triangle An Investigation March 20, 2008 Mario Soster

arxiv: v1 [math.co] 5 Jun 2015

1 Section 8.1: Sequences. 2 Section 8.2: Innite Series. 1.1 Limit Rules. 1.2 Common Sequence Limits. 2.1 Denition. 2.

SOME SHARP OSTROWSKI-GRÜSS TYPE INEQUALITIES

A GENERALIZATION OF GAUSS THEOREM ON QUADRATIC FORMS

Error-free compression

Math 2414 Activity 17 (Due with Final Exam) Determine convergence or divergence of the following alternating series: a 3 5 2n 1 2n 1

Chapter System of Equations

sin m a d F m d F m h F dy a dy a D h m h m, D a D a c1cosh c3cos 0

Limit of a function:

FACULTY OF MATHEMATICAL STUDIES MATHEMATICS FOR PART I ENGINEERING. Lectures

Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers Roy D. Yates and David J.

Supplemental Handout #1. Orthogonal Functions & Expansions

Existence of Nonoscillatory Solution of High Order Linear Neutral Delay Difference Equation

Certain sufficient conditions on N, p n, q n k summability of orthogonal series

2017/2018 SEMESTER 1 COMMON TEST

Pre-Calculus - Chapter 3 Sections Notes

Fig. 1. I a. V ag I c. I n. V cg. Z n Z Y. I b. V bg

Numerical Methods for Finding Multiple Solutions of a Superlinear Problem

FOURIER SERIES PART I: DEFINITIONS AND EXAMPLES. To a 2π-periodic function f(x) we will associate a trigonometric series. a n cos(nx) + b n sin(nx),

too many conditions to check!!

Transcription:

Itertio Jor of Scietific Reserch Egieerig & Techoogy (IJSRET ISSN 78 88 Vome 6 Isse 4 pri 7 44 SOLVING FUZZY LINER PROGRMMING PROBLEM USING SUPPORT ND CORE OF FUZZY NUMBERS Dr.S.Rmthigm K.Bmrg sst. Professor Deprtmet of mthemtics Periyr rts Coege Cddore Tmid Idi sst. Professor d Hed Deprtmet of Mthemtics chriy rts d Sciece Coege Pdcherry Emi: bmrgek@gmi.coom BSTRCT My thors sed differet types rkig fctio to sove fzzy ier progrmmig method. I this pper ew pproch hs bee proposed to sove fzzy ier progrmmed by sig spport d core of fzzy mbers withot sig membership fctio d ph ct techiqe. Differet types of probems were tke d soved by proposed method. Keywords Fzzy ier progrmmig probem Trpezoid d Trigr fzzy mber spport d core of fzzy mber.. INTRODUCTION The cocept of decisio-mkig i fzzy eviromet first proposed by R.E.Bem d L. Zdh []. Zimmer[] hs proposed the cocept of fzzy ier progrmmig. My thors proposed differet techiqe of sovig FLP probem i re time sittio. Meki [4] hs proposed ew method of sovig FLP probem sig rkig fctios. P.Rreshwri d Shy Sdh [8] proposed method to sove FFLP probem by Robst s rkig fctio d the compred their sotio with Pdi d Jykshmi [5] sotio who proposed ew method to sove FFLP probem.lter o Ide Hss ki d Frrh d [9] hs sed Meki [4] d Yker rkig fctios to sove FLP whe fzzy mbers i obective fctio coefficiets fzzy mbers i right-hd side coefficiets d fiy fzzy mbers i obective fctio coefficiets s we s i right-hd side coffeiciets..kmr d Sigh[7] proposed ew method for sovig fy fzzy ier progrmmig probems sig rkig fctio.. DEFINITIONS.. Membership fctio: Let R be the re ie. Let be the sbset of R. The fctio : R [ ] is kow s membership fctio o X. Fzzy set: Let X be set d be rbitrry eemet of X the fzzy sbset of X is mp : X [ ] (or is set of ordered pir ( where ( is membership fctio. X. Fzzy mber: fzzy set of R is sid to be trpezoid fzzy mber if the membership fctio hs the foowig chrcteristic. : R [ ] is cotios fctio.. ( ( c] [ d.. Stricty icresig o [c] d stricty decresig o [bd]. 4. ( [ b] Note: Trpezoid Fzzy mber becomes trigr fzzy mber whe =b.. ct: The ct of fzzy set is the crisp set tht cotis the eemets of X whose membership grde i re greter th or eq to the ve. i.e. (.4 Cove fzzy set: fzzy set o R is cove if ( ( y mi ( ( y d oy if y X d [ ].5 Spport of Fzzy mber: If is fzzy set the X ( d deoted by spport of Spp( or..6. Core of fzzy mber: If is fzzy set the core X ( d deoted by Cor( or of C(.

Itertio Jor of Scietific Reserch Egieerig & Techoogy (IJSRET ISSN 78 88 Vome 6 Isse 4 pri 7 45.7. verge of iterv: If [b] is sbset of R the verge of [ b] is defied s vg([b]= b. There re my wys of represetig the fzzy mbers. Bt most importty the fzzy mbers re represeted i two wys mey trigr fzzy mber d trpezoid fzzy mbers..8.trpezoid fzzy mber: Let s cosider the trpezoid mber s where or d its correspodig membership fctio is defied s foows ( ( ( esewhere The geometric represettio of trpezoid membership fctio for fzzy mber is show beow Fig-: Trpezoid Fzzy Nmber Here the spport of is S the core of is C (. ( d ( ( ( vg S d ( ( ( vg C ( Let s cosider the trpezoid mber s where or d its correspodig membership fctio is defied s foows ( ( ( esewhere The geometric represettio of trpezoid membership fctio for fzzy mber show beow Fig-: Trigr Fzzy Nmber Here the spport of is S core of is C(. ( vg ( is ( d the vg( C(..(.. Opertios of Trpezoid Fzzy Nmbers:- ssme tht d B b b re y two trpezoid fzzy mber the the rithmetic trpezoid fzzy mbers re defied s beow.9.trigr fzzy mber:

Itertio Jor of Scietific Reserch Egieerig & Techoogy (IJSRET ISSN 78 88 Vome 6 Isse 4 pri 7 46... dditio: B b b b b... Sbtrctio: B b b b b...scr Mtipictio: if d if..opertios of Trigr Fzzy Nmbers:- ssme tht d b B re y two trpezoid fzzy mber the the rithmetic trpezoid fzzy mbers re defied s beow...dditio: B b b...sbtrctio: B b b...scr Mtipictio: if d if..rkig fctio: The rkig fctio is the most powerf techiqe to compre the fzzy mbers. My types of rkig fctios itrodced by the my thors to sove fzzy ier progrmmig probem with fzzy prmeters. Let F(R be the set of fzzy mbers. The rkig fctio is defied by : F( R R. The compriso betwee the fzzy mbers d B is show beow. B iff ( ( B. B iff ( ( B. B iff ( ( B so stisfies the ier property s foows ( c B c( ( B where c R d B F( R... Spport d core with respect to Meki Rkig Fctio for Trpezoid fzzy mbers:- If is trpezoid fzzy mber the the Meki rkig fctio[4] for trpezoid fzzy mber is ( if sp d ( ( ( ( ( ( ( ( = vg ( + vg( C(.4.Spport d core with respect to Meki Rkig Fctio for Trigr fzzy mbers:- If is trigr fzzy mber the the Meki rkig fctio[4] for trigr fzzy mber is ( if sp d 4 ( = vg ( + C(

Itertio Jor of Scietific Reserch Egieerig & Techoogy (IJSRET ISSN 78 88 Vome 6 Isse 4 pri 7 47.5.Spport d core with respect to Robst s Rkig Fctio for Trpezoid fzzy mbers:- ( if sp d ( ( ( ( ( ( ( ( = vg( vg( C(.6.Spport d core with respect to Robst s Rkig Fctio for Trigr fzzy mbers:- If is trigr fzzy mber the the Robst s trigr fzzy mber is rkig fctio for ( if sp d 4 ( = vg( C(.6.Mthemtic formtio of Lier progrmmig Probem: The mthemtic ier progrmmig probem is stted s foows c M (or Mi z sbect to i or or b i=..m The bove mthemtic LPP is kow s crisp ier progrmmig probem. Here the prmeters re crisp ves. Some time the some or the prmeters re fzzy mbers the the crisp LPP becme fzzy ier progrmmig probem. So the mthemtic fzzy ier progrmmig probem s foows ~ i ~ c M (or Mi z sbect to ~ or or b Nmeric Empes: i=.m Where ~ c ~ i b ~ re fzzy mbers.. For symmetric trpezoid fzzy mber M z~ (48 ~ ( ~ (5 ~ sbect to ~ ~ ~ (7 ~ 4 ~ (6 ~ ~ ~ (59 ~ ~ ~ Usig Meki Rkig fctio Spport core d rkig fctio ve for the fzzy mber =(48ccted s beow S ( ( (4 8 ( ( ( ( vg S 6 48 C (

Itertio Jor of Scietific Reserch Egieerig & Techoogy (IJSRET ISSN 78 88 Vome 6 Isse 4 pri 7 48 ( ( ( (4 8 vg C 6 Meki Rkig fctio ve for =(48 is( vg( vgc( 6 6 Simir mer crisp ves for the remiig fzzy mber fod d ist i the tbe beow ( Fzzy C( vg vg mber( ( (C( ( (4 [] 4 (5 (-6 [5] 6 (7 (- [7] 4 4 8 (6 (8 [6] 4 4 8 (59 ( [59] 7 7 4 So the crisp LPP for the bove FLPP s give beow M z 4 sbect to 6 8 4 8 4 Where z re crisp vribes correspodig to fzzy vribes ~ z ~ ~ ~ Sovig the bove LPP sig simpe method we get =5.48 =.857 = d z=76.57 Usig Robst s Rkig fctio Spport core d rkig fctio ve for the fzzy mber =(48ccted s beow S ( ( (4 8 ( ( ( ( vg S 6 48 C ( ( ( ( (4 8 vg C 6 Robst s Rkig fctio ve for =(48 is( vg( vgc( 6 6 6 Simir mer crisp ves for the remiig fzzy mber fod d ist i the tbe beow ( Fzzy C( vg vg mber( ( (C( ( (4 [] (5 (-6 [5] (7 (- [7] 4 4 4 (6 (8 [6] 4 4 4 (59 ( [59] 7 7 7 So the crisp LPP for the bove FLPP s give beow M z 6 sbect to Where z 4 4 4 7 re crisp vribes correspodig to ~ ~ ~ fzzy vribes ~ z Sovig the bove LPP sig simpe method we get =.74 =.486 = d z= 9.49. For o-symmetric trpezoid fzzy mber M z~ (48 ~ ( ~ (5 ~ sbect to ~ ~ ~ (74 ~ 4 ~ (6 ~ ~ ~ (59 ~ ~ ~ Usig Meki Rkig fctio Spport core d rkig fctio ve for the fzzy mber =(48ccted s beow S ( ( (4 8 (9 ( 9 ( ( vg S 5 48 C (

Itertio Jor of Scietific Reserch Egieerig & Techoogy (IJSRET ISSN 78 88 Vome 6 Isse 4 pri 7 49 ( ( ( (4 8 vg C 6 ( vg( vgc( 5 6 Simir mer crisp ves for the remiig fzzy mber fod d ist i the tbe beow ( Fzzy mber( C( vg ( vg (C( ( (4 [] 4 (5 (-6 [5] 5 (74 (-9 [7] 4 7 (6 (9 [6] 5 4 9 (59 (4 [59] 8 7 5 So the crisp LPP for the bove FLPP s give beow M z 4 sbect to 5 4 9 7 5 re crisp vribes correspodig to ~ ~ Where fzzy vribes ~ Sovig the bove LPP sig simpe method we get =5.4 =.56 = d z=69.74 Usig Robst s Rkig fctio Spport core d rkig fctio ve for the fzzy mber =(48ccted s beow S ( ( (4 8 (9 ( 9 ( ( vg S 5 48 C ( ( ( ( (4 8 vg C 6 ( vg( vgc( 5 6 5. 5 Simir mer crisp ves for the remiig fzzy mber fod d ist i the tbe beow Fzzy mber( C( vg ( vg (C( ( (4 [] ( (5 (-6 [5].5 (74 (-9 [7] 4.5 (6 (9 [6] 5 4 4.5 (59 (4 [59] 8 7 7.5 So the crisp LPP for the bove FLPP s give beow M z 5.5. sbect to 5.5 4 4.5 7.5 re crisp vribes correspodig to Where fzzy vribes ~ ~ ~ Sovig the bove LPP sig simpe method we get =.574 =.649 = d z= 7.486 Now cosider trigr Fy Fzzy ier progrmmig probem the probem discssed i Rreshwri[8] M z~ ( ~ ~ (4 sbect to ( ~ ( ~ (7 ( ~ ( ~ (8 ~ ~ Sotio:- By Meki rkig fctiowe get the crisp LPP s foows M z 4 6 sbect to 4 4 4 6 The sotio is = 4.6667; =.6667; Z= 4.6667 By Robst s rkig fctio we get the crisp LPP s foows M z sbect to The sotio is = 4.6667; =.6667; Z=.. CONCLUSION I this pper we proposed ew method of sovig y kid Fzzy ier progrmmig probem withot sig ph ct method. Here we itrodced the ew techiqe

Itertio Jor of Scietific Reserch Egieerig & Techoogy (IJSRET ISSN 78 88 Vome 6 Isse 4 pri 7 5 spport d core of trpezoid d trigr fzzy mbers with differet types of probem. Whe compre with other proposed methods by vrios thors this wi be the simpest method of sovig y FLPP. We hve tke Meki rkig fctio d Robst s Rkig fctio for sovig FLPP. REFERENCES [] BemR.E d ZdhL. 97.Decisio mkig i fzzy eviromet.mgemet Scieces7(97 pp 4-64. [] ZimmermH.J 978.Fzzy progrmmig d ier progrmmig with sever obective fctios Fzzy sets d systems.(978pp:45-55 [] Yger R.R 98. procedre for orderig fzzy sbsets of the it iterv.iformtio secieces vo.4o:pp:4-6. [4] MekiH.R..Rkig fctios d their ppictios to fzzy ier progrmmig.fr Est Jor Mthemtics Scieces4(pp: 8- [5]Jykshmi. M Pdi P. New Method for fidig optim Fzzy Sotio for Fy Fzzy Lier Progrmmig Probems. Itertio Jor of Egieerig Reserch d ppictios (IJER ISSN:48-96 www.ier.com vo.isse 4 Jy- gst pp.47-54. [6]ZdehL.(965Fzzy sets iformtio d cotro 8(8-5. [7] Kmr d SighP. ew method for sovig fy fzzy ier progrmmig probems.s of fzzy Mthemtics d Iformtio vo. o. Jry pp:-8. [8]P.Rreswri d.shy Sdh-4 Sovig fy fzzy ier progrmmig probem by rkig. Itertio or of mthemtics treds d techoogy-vome 9 mber-my 4. [9]Ide Hss ki d Frrh d- 4.Rkig fctio methods for sovig fzzy ier progrmmig probems.mthemtictheory d modeig.issn 4-584(pper Vo 4No.44.