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Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
Facility Location Problem
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Facility Location Problem

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  • 1. ENDÜSTRİDE BİLGİSAYAR UYGULAMALARI - 2 New potential hubs in the South-Atlantic market. A problem of location Journal of Transport Geography Volume 11, Issue 2 , June 2003, Pages 139-149 FERİDE SEVLİ – 2000503052 AYTÜL ŞENER – 200503056 İLKEM YALINER – 2000503067
  • 2. İçerik:
    • Tesis Planlama Kavramı
    • Tesis Planlamanın Amaçları
    • Tesis Planlama Tipleri
    • Tesisin Kurulacağı Bölgenin Seçimi
    • Alternatiflerin Değerlendirilme Yöntemleri
    • Havacılık Sektöründe Tesis Planlama Uygulamaları
  • 3. TESİS PLANLAMA KAVRAMI:
    • TESİS : Mal ve hizmetlerin fiilen üretildiği fiziksel birimlerdir.
    • TESİS PLANLAMA : Tesislerin düzenleme çalışmalarının yapılması, tesisin kurulması ve faaliyete geçirilmesi aşamalarında gerçekleştirilecek olan faaliyetlerin bugünden eşgüdümlerinin yapılmasıdır.
  • 4. TESİS PLANLAMA AMAÇLARI:
    • Kaynakların kullanımı
    • Darboğazların belirlenmesi
    • Tesis faaliyetleri
    • Optimum yerleşim düzeni
          • Maliyet
          • Mesafe
          • Zaman
  • 5. TESİS PLANLAMA TİPLERİ:
    • Basit Yerleşim
    • Çoklu Yerleşim
    • Tesis Oluşturulması ve Kapasite Atama
    • Tesis Seçimi ve Kapasite Atama
    • Tesis İçi Yerleşim(QAP)
  • 6. TESİSİN KURULACAĞI BÖLGENİN SEÇİLMESİ:
    • Yerleşim Kararlarını Etkileyen Faktörler :
    • Ülke seçimi (kanunlar, pazar, işgücü, tedarik, alım gücü vb.)
    • Bölge seçimi (maliyet, çevre kuralları, müşteri&hammadde erişimi vb.)
    • Yer seçimi (yerin alan&maliyeti, ulaşım kolaylığı vb.)
  • 7. ALTERNATİFLERİ DEĞERLENDİRME YÖNTEMLERİ:
      • Faktör Oranlama Metodu
      • Başa-baş Analizi
      • Ağırlık Merkezi Metodu
      • Ulaştırma Metodu
  • 8. Problem:
    • Güney Amerika–Avrupa arasında
    • düzenlenen uçuş seferlerinde optimum
    • aktarma noktası seçimi
  • 9.  
  • 10. Veriler:
    • 1) Şehirler arası mesafeler
    0 4000 4100 24400 23100 21100 BUONES AIRES 4000 0 7000 21100 19500 17600 SAO PAULO 4100 7000 0 26200 24000 24000 SANTIAGO 24400 21100 26200 0 2500 3200 PARIS 23100 19500 24000 2500 0 1000 MADRID 21100 17600 24000 3200 1000 0 LISBON BUONES AIRES SAO PAULO SANTIAGO PARIS MADRID LİSBON TO FROM
  • 11. Veriler:
    • 2) Şehirler arası yolcu sayısı
    0 0 0 83000 270051 110000 BUONES AIRES 0 0 0 143977 126851 73847 SAO PAULO 0 0 0 82000 80054 95000 SANTIAGO 85000 155036 74000 0 0 0 PARIS 240213 126137 81220 0 0 0 MADRID 121000 69238 62000 0 0 0 LISBON BUONES AIRES SAO PAULO SANTIAGO PARIS MADRID LİSBON TO FROM
  • 12. min Σ (d E i H x + d H x S j ) T E i S j H x  E u S E i  E T *  S j  S
  • 13. Problemin Lingo Modeli:
    • SETS:
    • AIRPORT/LISBON MADRID PARIS SANTIAGO SAOPAULO BUONESAIRES/:HUB,K;
    • A(AIRPORT,AIRPORT):DIST,PASS;
    • ENDSETS
    • DATA:
    • DIST=0 1000 3200 24000 17600 21100
    • 1000 0 2500 24000 19500 23100
    • 3200 2500 0 26200 21100 24400
    • 24000 24000 26200 0 7000 4100
    • 17600 19500 21100 7000 0 4000
    • 21100 23100 24400 4100 4000 0 ;
    • PASS=0 0 0 62000 69238 121000
    • 0 0 0 81220 126137 240213
    • 0 0 0 74000 155036 85000
    • 95000 80054 82000 0 0 0
    • 73847 126851 143977 0 0 0
    • 110000 270051 83000 0 0 0 ;
    • ENDDATA
    • MIN=@SUM(AIRPORT(I):HUB(I)*K(I));
    • @FOR(AIRPORT(I):@SUM(A(J,K)|J#NE#I #AND# #NE#K:(DIST(J,I)+DIST(I,K))*PASS(J,K))=HUB(I));
    • IFA=@MIN(AIRPORT(I):HUB(I));
    • @FOR(AIRPORT(I)|HUB(I)#LE#IFA:K(I)=1);
    • @FOR(AIRPORT(I):@BIN(K(I)));
  • 14. Lingo Çözümü:
    • Rows= 1 Vars= 5 No. integer vars= 5 ( all are linear)
    • Nonzeros= 6 Constraint nonz= 0( 0 are +- 1) Density=1.000
    • Smallest and largest elements in absolute value= 0.317284E+11 0.481254E
    • No. < : 0 No. =: 0 No. > : 0, Obj=MIN, GUBs <= 0
    • Single cols= 5
    • Optimal solution found at step: 0
    • Objective value: 0.2743843E+11
    • Branch count: 0
    • Variable Value Reduced Cost
    • IFA 0.2743843E+11 0.0000000E+00
    • HUB( LISBON) 0.3455933E+11 0.0000000E+00
    • HUB( MADRID) 0.2743843E+11 0.0000000E+00
    • HUB( PARIS) 0.3879355E+11 0.0000000E+00
    • HUB( SANTIAGO) 0.4812541E+11 0.0000000E+00
    • HUB( SAOPAULO) 0.3371716E+11 0.0000000E+00
    • HUB( BUONESAIRES) 0.3172843E+11 0.0000000E+00
    • K( LISBON) 0.0000000E+00 0.3455933E+11
    • K( MADRID) 1.000000 0.0000000E+00
    • K( PARIS) 0.0000000E+00 0.3879355E+11
    • K( SANTIAGO) 0.0000000E+00 0.4812541E+11
    • K( SAOPAULO) 0.0000000E+00 0.3371716E+11
    • K( BUONESAIRES) 0.0000000E+00 0.3172843E+11
  • 15. Lingo Çözümü:
    • DIST( LISBON, LISBON) 0.0000000E+00 0.0000000E+00
    • DIST( LISBON, MADRID) 1000.000 0.0000000E+00
    • DIST( LISBON, PARIS) 3200.000 0.0000000E+00
    • DIST( LISBON, SANTIAGO) 24000.00 0.0000000E+00
    • DIST( LISBON, SAOPAULO) 17600.00 0.0000000E+00
    • DIST( LISBON, BUONESAIRES) 21100.00 0.0000000E+00
    • DIST( MADRID, LISBON) 1000.000 0.0000000E+00
    • DIST( MADRID, MADRID) 0.0000000E+00 0.0000000E+00
    • DIST( MADRID, PARIS) 2500.000 0.0000000E+00
    • DIST( MADRID, SANTIAGO) 24000.00 0.0000000E+00
    • DIST( MADRID, SAOPAULO) 19500.00 0.0000000E+00
    • DIST( MADRID, BUONESAIRES) 23100.00 0.0000000E+00
    • DIST( PARIS, LISBON) 3200.000 0.0000000E+00
    • DIST( PARIS, MADRID) 2500.000 0.0000000E+00
    • DIST( PARIS, PARIS) 0.0000000E+00 0.0000000E+00
    • DIST( PARIS, SANTIAGO) 26200.00 0.0000000E+00
    • DIST( PARIS, SAOPAULO) 21100.00 0.0000000E+00
    • DIST( PARIS, BUONESAIRES) 24400.00 0.0000000E+00
    • DIST( SANTIAGO, LISBON) 24000.00 0.0000000E+00
    • DIST( SANTIAGO, MADRID) 24000.00 0.0000000E+00
    • DIST( SANTIAGO, PARIS) 26200.00 0.0000000E+00
    • DIST( SANTIAGO, SANTIAGO) 0.0000000E+00 0.0000000E+00
    • DIST( SANTIAGO, SAOPAULO) 7000.000 0.0000000E+00
    • DIST( SANTIAGO, BUONESAIRES) 4100.000 0.0000000E+00
  • 16. Lingo Çözümü:
    • DIST( SAOPAULO, LISBON) 17600.00 0.0000000E+00
    • DIST( SAOPAULO, MADRID) 19500.00 0.0000000E+00
    • DIST( SAOPAULO, PARIS) 21100.00 0.0000000E+00
    • DIST( SAOPAULO, SANTIAGO) 7000.000 0.0000000E+00
    • DIST( SAOPAULO, SAOPAULO) 0.0000000E+00 0.0000000E+00
    • DIST( SAOPAULO, BUONESAIRES) 4000.000 0.0000000E+00
    • DIST( BUONESAIRES, LISBON) 21100.00 0.0000000E+00
    • DIST( BUONESAIRES, MADRID) 23100.00 0.0000000E+00
    • DIST( BUONESAIRES, PARIS) 24400.00 0.0000000E+00
    • DIST( BUONESAIRES, SANTIAGO) 4100.000 0.0000000E+00
    • DIST( BUONESAIRES, SAOPAULO) 4000.000 0.0000000E+00
    • DIST( BUONESAIRES, BUONESAIRES 0.0000000E+00 0.0000000E+00
    • PASS( LISBON, LISBON) 0.0000000E+00 0.0000000E+00
    • PASS( LISBON, MADRID) 0.0000000E+00 0.0000000E+00
    • PASS( LISBON, PARIS) 0.0000000E+00 0.0000000E+00
    • PASS( LISBON, SANTIAGO) 62000.00 0.0000000E+00
    • PASS( LISBON, SAOPAULO) 69238.00 0.0000000E+00
    • PASS( LISBON, BUONESAIRES) 121000.0 0.0000000E+00
    • PASS( MADRID, LISBON) 0.0000000E+00 0.0000000E+00
    • PASS( MADRID, MADRID) 0.0000000E+00 0.0000000E+00
    • PASS( MADRID, PARIS) 0.0000000E+00 0.0000000E+00
    • PASS( MADRID, SANTIAGO) 81220.00 0.0000000E+00
    • PASS( MADRID, SAOPAULO) 126137.0 0.0000000E+00
    • PASS( MADRID, BUONESAIRES) 240213.0 0.0000000E+00
  • 17. Lingo Çözümü:
    • PASS( PARIS, LISBON) 0.0000000E+00 0.0000000E+00
    • PASS( PARIS, MADRID) 0.0000000E+00 0.0000000E+00
    • PASS( PARIS, PARIS) 0.0000000E+00 0.0000000E+00
    • PASS( PARIS, SANTIAGO) 74000.00 0.0000000E+00
    • PASS( PARIS, SAOPAULO) 155036.0 0.0000000E+00
    • PASS( PARIS, BUONESAIRES) 85000.00 0.0000000E+00
    • PASS( SANTIAGO, LISBON) 95000.00 0.0000000E+00
    • PASS( SANTIAGO, MADRID) 80054.00 0.0000000E+00
    • PASS( SANTIAGO, PARIS) 82000.00 0.0000000E+00
    • PASS( SANTIAGO, SANTIAGO) 0.0000000E+00 0.0000000E+00
    • PASS( SANTIAGO, SAOPAULO) 0.0000000E+00 0.0000000E+00
    • PASS( SANTIAGO, BUONESAIRES) 0.0000000E+00 0.0000000E+00
    • PASS( SAOPAULO, LISBON) 73847.00 0.0000000E+00
    • PASS( SAOPAULO, MADRID) 126851.0 0.0000000E+00
    • PASS( SAOPAULO, PARIS) 143977.0 0.0000000E+00
    • PASS( SAOPAULO, SANTIAGO) 0.0000000E+00 0.0000000E+00
    • PASS( SAOPAULO, SAOPAULO) 0.0000000E+00 0.0000000E+00
    • PASS( SAOPAULO, BUONESAIRES) 0.0000000E+00 0.0000000E+00
    • PASS( BUONESAIRES, LISBON) 110000.0 0.0000000E+00
    • PASS( BUONESAIRES, MADRID) 270051.0 0.0000000E+00
    • PASS( BUONESAIRES, PARIS) 83000.00 0.0000000E+00
    • PASS( BUONESAIRES, SANTIAGO) 0.0000000E+00 0.0000000E+00
    • PASS( BUONESAIRES, SAOPAULO) 0.0000000E+00 0.0000000E+00
    • PASS( BUONESAIRES, BUONESAIRES 0.0000000E+00 0.0000000E+00
  • 18. Lingo Çözümü:
    • Row Slack or Surplus Dual Price
    • 1 0.2743843E+11 -1.000000
    • 2 0.0000000E+00 0.0000000E+00
    • 3 0.0000000E+00 1.000000
    • 4 0.0000000E+00 0.0000000E+00
    • 5 0.0000000E+00 0.0000000E+00
    • 6 0.0000000E+00 0.0000000E+00
    • 7 0.0000000E+00 0.0000000E+00
    • 8 0.0000000E+00 0.0000000E+00
    • 9 0.0000000E+00 -0.2743843E+11
  • 19. Problem:
    • Avrupa – Güney Amerika arasında
    • düzenlenen uçuş seferlerinde; biri Amerika
    • diğeri Avrupa’da olmak üzere iki tane
    • aktarma noktası seçimi
  • 20.  
  • 21. min Σ (d E j E x + d E x S y + d S y S j ) T E i S j E x ,S y  E x S E i  E T *  S j  S
  • 22. Problemin Lingo Modeli:
    • SETS:
    • S1/LISBON MADRID PARIS/;
    • S2/SANTIAGO SAOPAULO BUONESAIRES/;
    • B1(S1,S1):DIST1;
    • B2(S2,S2):DIST2;
    • A(S1,S2):DIST,PASS,HUB,AFI;
    • ENDSETS
    • DATA:
    • DIST1= 0 1000 3200
    • 1000 0 2500
    • 3200 2500 0 ;
    • DIST2= 0 7000 4100
    • 7000 0 4000
    • 4100 4000 0 ;
    • DIST= 24000 17600 21100
    • 24000 19500 23100
    • 26200 21100 24400;
    • PASS= 157000 143085 231000
    • 161274 252988 425087
    • 156000 384190 168000;
    • ENDDATA
    • MIN=@SUM(A(I,J):HUB(I,J)*AFI(I,J));
    • @FOR(A(I,J):@SUM(A(K,L):(DIST1(K,I)+DIST(I,J)+DIST2(J,L))*PASS(K,L))=HUB(I,J));
    • IFA=@MIN(A(I,L):HUB(I,L));
    • @FOR(A(M,N)|HUB(M,N)#LE#IFA:AFI(M,N)=1);
    • @FOR(A(I,J):@BIN(AFI(I,J)));
  • 23. Lingo Çözümü:
    • Rows= 1 Vars= 8 No. integer vars= 8 ( all are linear)
    • Nonzeros= 9 Constraint nonz= 0( 0 are +- 1) Density=1.000
    • Smallest and largest elements in absolute value= 0.494510E+11 0.670984E
    • No. < : 0 No. =: 0 No. > : 0, Obj=MIN, GUBs <= 0
    • Single cols= 8
    • Optimal solution found at step: 0
    • Objective value: 0.4630561E+11
    • Branch count: 0
    • Variable Value Reduced Cost
    • IFA 0.4630561E+11 0.0000000E+00
    • DIST1( LISBON, LISBON) 0.0000000E+00 0.0000000E+00
    • DIST1( LISBON, MADRID) 1000.000 0.0000000E+00
    • DIST1( LISBON, PARIS) 3200.000 0.0000000E+00
    • DIST1( MADRID, LISBON) 1000.000 0.0000000E+00
    • DIST1( MADRID, MADRID) 0.0000000E+00 0.0000000E+00
    • DIST1( MADRID, PARIS) 2500.000 0.0000000E+00
    • DIST1( PARIS, LISBON) 3200.000 0.0000000E+00
    • DIST1( PARIS, MADRID) 2500.000 0.0000000E+00
    • DIST1( PARIS, PARIS) 0.0000000E+00 0.0000000E+00
  • 24. Lingo Çözümü:
    • DIST2( SANTIAGO, SANTIAGO) 0.0000000E+00 0.0000000E+00
    • DIST2( SANTIAGO, SAOPAULO) 7000.000 0.0000000E+00
    • DIST2( SANTIAGO, BUONESAIRES) 4100.000 0.0000000E+00
    • DIST2( SAOPAULO, SANTIAGO) 7000.000 0.0000000E+00
    • DIST2( SAOPAULO, SAOPAULO) 0.0000000E+00 0.0000000E+00
    • DIST2( SAOPAULO, BUONESAIRES) 4000.000 0.0000000E+00
    • DIST2( BUONESAIRES, SANTIAGO) 4100.000 0.0000000E+00
    • DIST2( BUONESAIRES, SAOPAULO) 4000.000 0.0000000E+00
    • DIST2( BUONESAIRES, BUONESAIRE 0.0000000E+00 0.0000000E+00
    • DIST( LISBON, SANTIAGO) 24000.00 0.0000000E+00
    • DIST( LISBON, SAOPAULO) 17600.00 0.0000000E+00
    • DIST( LISBON, BUONESAIRES) 21100.00 0.0000000E+00
    • DIST( MADRID, SANTIAGO) 24000.00 0.0000000E+00
    • DIST( MADRID, SAOPAULO) 19500.00 0.0000000E+00
    • DIST( MADRID, BUONESAIRES) 23100.00 0.0000000E+00
    • DIST( PARIS, SANTIAGO) 26200.00 0.0000000E+00
    • DIST( PARIS, SAOPAULO) 21100.00 0.0000000E+00
    • DIST( PARIS, BUONESAIRES) 24400.00 0.0000000E+00
    • PASS( LISBON, SANTIAGO) 157000.0 0.0000000E+00
    • PASS( LISBON, SAOPAULO) 143085.0 0.0000000E+00
    • PASS( LISBON, BUONESAIRES) 231000.0 0.0000000E+00
    • PASS( MADRID, SANTIAGO) 161274.0 0.0000000E+00
    • PASS( MADRID, SAOPAULO) 252988.0 0.0000000E+00
    • PASS( MADRID, BUONESAIRES) 425087.0 0.0000000E+00
  • 25. Lingo Çözümü:
    • PASS( PARIS, SANTIAGO) 156000.0 0.0000000E+00
    • PASS( PARIS, SAOPAULO) 384190.0 0.0000000E+00
    • PASS( PARIS, BUONESAIRES) 168000.0 0.0000000E+00
    • HUB( LISBON, SANTIAGO) 0.6183313E+11 0.0000000E+00
    • HUB( LISBON, SAOPAULO) 0.4630561E+11 0.0000000E+00
    • HUB( LISBON, BUONESAIRES) 0.5203010E+11 0.0000000E+00
    • HUB( MADRID, SANTIAGO) 0.6102913E+11 0.0000000E+00
    • HUB( MADRID, SAOPAULO) 0.4945099E+11 0.0000000E+00
    • HUB( MADRID, BUONESAIRES) 0.5538335E+11 0.0000000E+00
    • HUB( PARIS, SANTIAGO) 0.6709839E+11 0.0000000E+00
    • HUB( PARIS, SAOPAULO) 0.5427308E+11 0.0000000E+00
    • HUB( PARIS, BUONESAIRES) 0.5958185E+11 0.0000000E+00
    • AFI( LISBON, SANTIAGO) 0.0000000E+00 0.6183313E+11
    • AFI( LISBON, SAOPAULO) 1.000000 0.0000000E+00
    • AFI( LISBON, BUONESAIRES) 0.0000000E+00 0.5203010E+11
    • AFI( MADRID, SANTIAGO) 0.0000000E+00 0.6102913E+11
    • AFI( MADRID, SAOPAULO) 0.0000000E+00 0.4945099E+11
    • AFI( MADRID, BUONESAIRES) 0.0000000E+00 0.5538335E+11
    • AFI( PARIS, SANTIAGO) 0.0000000E+00 0.6709839E+11
    • AFI( PARIS, SAOPAULO) 0.0000000E+00 0.5427308E+11
    • AFI( PARIS, BUONESAIRES) 0.0000000E+00 0.5958185E+11
  • 26. Lingo Çözümü:
    • Row Slack or Surplus Dual Price
    • 1 0.4630561E+11 -1.000000
    • 2 0.0000000E+00 0.0000000E+00
    • 3 0.0000000E+00 1.000000
    • 4 0.0000000E+00 0.0000000E+00
    • 5 0.0000000E+00 0.0000000E+00
    • 6 0.0000000E+00 0.0000000E+00
    • 7 0.0000000E+00 0.0000000E+00
    • 8 0.0000000E+00 0.0000000E+00
    • 9 0.0000000E+00 0.0000000E+00
    • 10 0.0000000E+00 0.0000000E+00
    • 11 0.0000000E+00 0.0000000E+00
    • 12 0.0000000E+00 -0.4630561E+11
  • 27. TEŞEKKÜRLER :))

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