Discrete location problems with flexible objectives:
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| Schriftenreihe: | Schriftenreihe Logistik-Management in Forschung und Praxis
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| 100 | 1 | |a Velten, Sebastian |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Discrete location problems with flexible objectives |c Sebastian Velten |
| 264 | 1 | |a Hamburg |b Kovač |c 2009 | |
| 300 | |a XII, 341 S. |b graph. Darst. | ||
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| 650 | 7 | |a Betriebliche Standortwahl |2 stw | |
| 650 | 7 | |a Diskrete Entscheidung |2 stw | |
| 650 | 7 | |a Heuristisches Verfahren |2 stw | |
| 650 | 7 | |a Mathematische Optimierung |2 stw | |
| 650 | 4 | |a Operations Research - Standorttheorie - Lineare Optimierung - Logistik | |
| 650 | 7 | |a Transportproblem |2 stw | |
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Datensatz im Suchindex
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| adam_text | Titel: Discrete location problems with flexible objectives
Autor: Velten, Sebastian
Jahr: 2009
Contents
1 Introduction 1
1.1 The Concept of Flexible Objectives...................... 3
1.2 Elements of Location Theory.......................... 6
1.2.1 Continuous and Network Location................... 8
1.2.2 Discrete Facility Location....................... 11
1.3 Overview..................................... 18
Part I Location Problems without Capacities
2 The Discrete Ordered Median Problem without Capacities 23
2.1 Problem Formulation.............................. 23
2.2 Important Special Cases............................ 27
2.2.1 Pull Objectives............................. 28
2.2.2 Push Objectives............................. 32
2.2.3 Push-Pull Objectives.......................... 35
2.2.4 Balancing Objectives.......................... 37
2.3 Different Perspectives.............................. 44
2.4 Previous Modeling and Solution Approaches................. 49
2.4.1 A Quadratic Integer Programming Formulation........... 50
2.4.2 Several Linearizations ......................... 52
2.4.3 A Branch Bound Procedure..................... 56
2.4.4 Heuristic Solution Approaches..................... 59
2.5 Summary .................................... 62
3 Models and Algorithms Based on a Covering Approach 63
3.1 The Covering Approach for Non-Negative Modeling Weights........ 64
3.1.1 Decision Variables ........................... 64
3.1.2 Constraints and Objective....................... 67
3.1.3 The Complete Model.......................... 70
3.1.4 Variable Fixing............................. 73
3.1.5 Valid Inequalities............................ 79
3.1.6 A Specialized Branch Cut Procedure................ 81
3.1.7 Computational Study.......................... 83
ix
CONTENTS
3.2 A Reduced Formulation for A-Vectors Containing Zeros........... 94
3.2.1 Reformulation.............................. 94
3.2.2 Adjustment of Variable Fixing and Valid Inequalities........ 99
3.2.3 The Specialized Branch Cut Procedure for the Reduced Formulation 105
3.2.4 Computational Study.......................... 107
3.3 The Covering Approach for Real-Valued Modeling Weights......... 110
3.3.1 Model Extensions............................ 110
3.3.2 Variable Fixing............................. 115
3.3.3 Valid Inequalities and Specialized Branch Cut........... 124
3.3.4 Computational Study.......................... 130
3.4 Summary .................................... 137
4 Models and Algorithms Based on an Alternative Approach 139
4.1 Basic Concept and Model for A-Vectors Sorted in Non-Decreasing Sequence 140
4.1.1 Basic Concept.............................. 140
4.1.2 The Model for A-Vectors with Elements Sorted in Non-Decreasing
Sequence................................. 141
4.2 Several Reformulations for General A-Vectors................. 148
4.2.1 A Maximin Approach.......................... 148
4.2.2 An Approach Using the Allocation Variables............. 154
4.2.3 Extension to A-Vectors with One or More Negative Entries..... 159
4.2.4 Further Extensions and the Supplier Point of View......... 105
4.3 Two Solution Approaches ........................... 168
4.3.1 A Solution Approach Based on Variable Fixing ........... 169
4.3.2 A Solution Approach Using the BEAMR Concept.......... 175
4.4 Computational Study.............................. 185
4.4.1 Results for Problem Instances with Non-Negative A-Vec-tors .... 185
4.4.2 Results for Problem Instances with A-Vectors Containing Negative
Elements................................. 195
4.4.3 Suitability of the Respective Solution Concepts........... 198
4.5 Summary .................................... 198
Part II Capacitated Planning - Allocation and Location
5 The Ordered Transportation Problem 203
5.1 Introduction................................... 203
5.2 Problem Formulation and Complexity Results................ 204
5.2.1 Formal Definition............................ 204
CONTENTS
5.2.2 A (Mixed-) Integer Linear Programming Formulation........ 208
5.2.3 Complexity............................... 211
5.3 A Heuristic and an Exact Solution Approach................. 213
5.3.1 A Simple Exchange Heuristic ..................... 213
5.3.2 An Exact Solution Approach Based on the BEAMR Concept .... 21G
5.4 Computational Study.............................. 222
5.4.1 Results for the Heuristic Approach.................. 223
5.4.2 Results for the Exact Approaches................... 227
5.5 Summary .................................... 229
6 The Capacitated Ordered Median Problem 231
6.1 Introduction................................... 231
6.2 Problem Definition and Different Perspectives................ 232
6.2.1 Formal Definition............................ 232
6.2.2 Different Perspectives.......................... 236
6.3 Mixed-)Integer Linear Programming Formulations.............. 240
6.4 A Heuristic and an Exact Solution Procedure ................ 248
6.4.1 A Heuristic Solution Approach Using a VNS............. 248
6.4.2 An Exact Solution Approach Based on the BEAMR Concept .... 252
6.5 Computational Study.............................. 257
6.5.1 Results for the VNS Based Heuristic Procedure........... 258
6.5.2 Outcomes for the Exact Solution Approaches............. 264
6.5.3 Results for the CDOMP-MCO..................... 267
6.6 Summary .................................... 270
7 Conclusions and Further Research 271
7.1 Conclusions................................... 271
7.2 Further Research Topics............................ 273
7.2.1 Multi-Echelon Location Planning with Flexible Objectives..... 273
7.2.2 Vehicle Routing with a Flexible Objective.............. 276
A Computer and Test Instances 279
A.I Computer and Software ............................ 279
A.2 Test Instances.................................. 279
B Tables with Complete Results 283
B.I Tables for Chapter 3.............................. 283
B.I.I Tables for Section 3.1.7......................... 283
CONTENTS
B.1.2 Tables for Section 3.2.4......................... 290
B.1.3 Tables for Section 3.3.4......................... 293
B.2 Tables for Chapter 4.............................. 297
B.2.1 Tables for Section 4.4.1......................... 297
B.2.2 Tables for Section 4.4.2......................... 299
B.3 Tables for Chapter 5.............................. 301
B.3.1 Tables for Section 5.4.1......................... 301
B.3.2 Tables for Section 5.4.2......................... 307
B.4 Tables for Chapter 6.............................. 311
B.4.1 Tables for Section 6.5.1......................... 311
B.4.2 Tables for Section 6.5.2......................... 314
B.4.3 Tables for Section 6.5.3......................... 319
List of Tables 323
List of Figures 329
List of Algorithms 331
Bibliography 333
List of Tables
3.1 Tested Modeling Vectors: Covering Model and A 0............. 85
3.2 Results for the UDOMP: (COV - DOMPA 0) and Specialized Branch Cut
(ALL) (A/= 30,50; N = 3,5, M/S]; A2,A4).................. 86
3.3 Results for the UDOMP: (COV - DOMPA 0) and Specialized Branch k Cut
(ONE) (M = 30,50; N = 3,5, M/3 , A2,A4).................. 87
3.4 Results for the UDOMP: (COV - DOMPA 0) and Specialized Branch Cut
(ONEBIN) (M = 30,50; iV = 3, 5, [M/3 |; A2,A4)............... 87
3.5 Results for the UDOMP: CPLEX, CPLEX + Var. Fix., and Spec. B. C. . 88
3.6 Results for the UDOMP: Average Number of Fixed Variables (A 0). . . . 89
3.7 Results for the UDOMP: Improvement of the Root Node Gap........ 90
3.8 Results for the UDOMP: Comparison with Previous Results......... 91
3.9 Tested Modeling Vectors: Reduced Covering Model and A 0........ 109
3.10 Tested Modeling Vectors: (Reduced) Covering Model and A 6 RM...... 133
3.11 Results for the UDOMP: (COV - DOMPAeR«) and MlP-solver of CPLEX
(M = 15; N = 3,5; A7-A9, Arbitrary Costs).................. 133
3.12 Results for the UDOMP: (COV - DOMPAeRM) and CPLEX + Var. Fix.
(M = 15; N = 3,5; A7-A9, Arbitrary Costs).................. 134
3.13 Results for the UDOMP: Average Number of Fixed Variables (A 6 RA )- • 134
3.14 Results for UDOMP: (COV - DOMPAeRM) and Specialized Branch Cut
(M = 15; N = 3,5; A7-A9)............................ 134
3.15 Results for UDOMP: (COV - DOMPA€Rm) and CPLEX + Var. Fix. (A/ =
20; N = [M/31; A7-A9).............................. 135
3.16 Results for UDOMP: (COV - DOMPAeR«) and Specialized Branch k Cut
(M = 20; N = ( M/31; A7-A9).......................... 135
4.1 Results for the UDOMP: (ALT - DOMP ^rm) and Variable Fixing (A/ =
30; N = 3,5, ( A//3]; A4-A6)........................... 187
4.2 Results for the UDOMP: (ALT - DOMP2A 0) and Variable Fixing (M = 30;
N = 3,5, [Af/31; A4-A«)............................. 187
4.3 Results for the UDOMP: (ALT - DOMP3A£Rm) and Variable Fixing (M =
30; N = 3,5, fM/3 |; A4-A«)........................... 188
4.4 Results for the UDOMP: (ALT - DOMP^rm) and BEAMR (M = 30;
N = 3,5, fA//3]; A4-Ae)............................. 188
323
324___________________________________________________________LIST OF TABLES
4.5 Results for the UDOMP: (ALT - DOMP2A 0) and BEAMR (M = 30; N =
3,5, [M/31; A4-A6)................................ 189
4.6 Results for the UDOMP: (ALT - DOMP3A6Rm) and BEAMR (M = 30;
N = 3,5, [M/31; A4-A6)............................. 189
4.7 Results for the UDOMP: (ALT - D0MP3A£Rm) and Variable Fixing (M =
50; N = 3,5, M/3]; A4)............................. 190
4.8 Results for the UDOMP: (ALT - DOMP3AeRM) and BEAMR (M = 30;
N = 3,5, [M/31; A4)............................... 190
4.9 Results for the UDOMP: (ALT-DOMPA ) and Variable Fixing (M =
30,50; N = 3,5, [M/31; A1-A3)......................... 191
4.10 Results for the UDOMP: (ALT-DOMPA ) and BEAMR (M = 30,50;
N = 3,5, [M/31; A1-A3)............................. 192
4.11 Results for the UDOMP: Comparison Covering and Alternative Approach
(Arbitrary Costs and A 0)........................... 193
4.12 Results for the UDOMP: Comparison Covering and Alternative Approach
(Euclidean Distance Based Costs and A 0).................. 194
4.13 Results for the UDOMP: Comparison Covering and Alternative Approach
(Benchmark Test Instances and A 0)..................... 194
4.14 Results for the UDOMP: (ALT - DOMP1AeR«) and Variable Fixing (M =
20,30; N = 3,5, [M/31; A7-A9; Arbitrary Costs)................ 196
4.15 Results for the UDOMP: (ALT - DOMP3A€R«) and BEAMR (M = 20, 30;
N = 3,5, [M/31; A7-A9; Arbitrary Costs).................... 196
4.16 Results for the UDOMP: Comparison Covering and Alternative Approach
(Arbitrary Costs and A 6 RA/)......................... 197
4.17 Results for the UDOMP: Comparison Covering and Alternative Approach
(Euclidean Distance Based Costs and A G RM)................ 198
4.18 Suitability of Solution Concepts......................... 199
5.1 Tested Modeling Vectors: OTP......................... 223
5.2 Results for the OTP: Algorithm 5.1 with Initial Order (M = 100; N =
3.5.[A//31. M/2; A4-A6)............................. 224
5.3 Results for the OTP: Algorithm 5.1 with k = 1 (M = 100; TV = 3,5, [M/31,
M/2; A4-A6).................................... 224
5.4 Results for the OTP: Algorithm 5.1 with it = 2 (M = 100; N = 3,5, [M/31,
M/2; A4-Ae).................................... 225
5.5 Results for the OTP: Times Needed by the MlP-Solver of CPLEX to Reach
the Heuristic Objective Values.........................227
LIST OF TABLES___________________________________________________ 325
6.1 Results for the CDOMP: VNS Based Heuristic (M = 50; N = 3,5, [AT/31;
h-^e)....................................... 258
6.2 Results for the CDOMP: Development/Comparison of Solution Times: VNS
Based Heuristic, MlP-Solver of CPLEX, BEAMR (AT = 30,50,80; N =
3,5, TM/31; A^A).............................. 260
6.3 Results for the CDOMP: Comparison of the Deviation from a Total Bal-
ance: VNS Based Heuristic and MlP-Solver of CPLEX (AT = 50,80; N =
3,5,[M/31;A7-A9)................................ 262
6.4 Results for the CDOMP: Development/Comparison of Solution Times: VNS
Based Heuristic and MlP-Solver of CPLEX (M = 30, 50,80; N = 3, 5, f A//3];
A7-A9)....................................... 263
6.5 Results for the CDOMP: Development/Comparison of Solution Times: MIP-
Solver of CPLEX and BEAMR (AT = 30,50,80; N = 3,5, [AT/31; A^.A,,). 265
6.6 Number of BEAMR Iterations: UDOMP vs. CDOMP (M = 30, 50; N =
3,5, [AT/31; Aj-Ae)................................ 266
6.7 Results for the CDOMP-MCO: VNS Based Heuristic and MlP-Solver of
CPLEX (AT = 20; N = 3,5, [AT/31; A2,A4,A5,A9)...............268
6.8 Results for the CDOMP-MCO: Development of Heuristic Solution Times
(M = 30,50,80; N = 3,5, [AT/31; A2,A4.A7).................. 269
A.I Tested Modeling Vectors............................. 282
B.I Results for the UDOMP: (COV - DOMPA 0) and Specialized Branch Cut
(AT = 30,50; N = 3,5; Aj - A6; Arbitrary Costs)...............283
B.2 Results for the UDOMP: (COV - DOMPx o) and Specialized Branch Cut
(M = 80,100; TV = 3, 5; Ai - A6; Arbitrary Casts)...............284
B.3 Results for the UDOMP: (COV - DOMPA 0) and CPLEX + Var. Fix.
(M = 30,50, 80,100; AT = [A//3]; Ai-Ae; Arbitrary Costs).........285
B.4 Results for the UDOMP: (COV - DOMPA o) and Specialized Branch Cut
(Af = 30, 50; N = 3, 5; Ai - A6; Euclidean Distance Based Costs)......286
B.5 Results for the UDOMP: (COV - DOMPA 0) and Specialized Branch Cut
(AT = 80,100; N = 3,5; Ai - Ae; Euclidean Distance Based Costs)...... 287
B.6 Results for the UDOMP: (COV - DOMPA 0) and CPLEX + Var. Fix.
(AT = 30,50,80,100; N = [AT/31; i - * Euclidean Distance Based Costs). 288
B.7 Results for the UDOMP: (COV - DOMPA 0) and Specialized Branch k Cut
(pmedl, pmed2, pmed3; Ai-Ae).........................289
B.8 Results for the UDOMP: (COV - DOMPA 0) and CPLEX + Var. Fix.
(pmed4, pmed5, pmedlO; Ai-Ae)........................289
326___________________________________________________________LIST OF TABLES
B.9 Results for the UDOMP: (COV - DOMPA 0) and Specialized Branch Cut
(M = 50,80,100; JV = 3,5; A2 - A4; Arbitrary Costs)............. 290
B.10 Results for the UDOMP: (COV - DOMPA 0) and CPLEX + Var. Fix.
(M = 50, 80,100; N = M/3]; A2 - A4; Arbitrary Costs)...........290
B.ll Results for the UDOMP: (COV - DOMPA 0) and Specialized Branch Cut
(M = 50,80,100; JV = 3,5; A2 - A4; Euclidean Distance Based Costs). ... 291
B.12 Results for the UDOMP: (COV - DOMPA 0) and CPLEX + Var. Fix.
(M = 50,80,100; N = fM/3]; A2 - A4; Euclidean Distance Based Costs). . 291
B.13 Results for the UDOMP: (COV - DOMPrA 0) and Specialized Branch Cut
(pinedl, pmed2, pmed3; A2-A4)......................... 292
B.14 Results for the UDOMP: (COV - DOMPA 0) and Specialized Branch Cut
(pmed4, pmed5, pmedlO; A2-A4)........................292
B.15 Results for the UDOMP: (COV - DOMPA£RM) and Specialized Branch k.
Cut (M = 20,30,50, 80; JV = 3,5; A7-A9; Arbitrary Costs)..........293
B.16 Results for the UDOMP: (COV - DOMPAeRM) and CPLEX + Var.Fix.
(M = 20,30,50, 80; JV = M/$ ; A7-A9; Arbitrary Costs)........... 293
B.17 Results for the UDOMP: (COV - D0MPA(eRm) and Specialized Branch
Cut (M = 20,30,50, 80; JV = 3, 5; A7-A9; Euclidean Distance Based Costs). 294
B.18 Results for the UDOMP: (COV - DOMPAeRM) and CPLEX + Var.Fix.
(A/ = 20,30,50, 80; JV = M/$ ; A7-A9; Euclidean Distance Based Costs). . 294
B.19 Results for the UDOMP: (COV - DOMPrA€RM) and Specialized Branch
Cut (M = 20,30, 50,80; iV = 3,5; A7; Arbitrary Costs)............ 295
B.20 Results for the UDOMP: (COV - D0MPA£Rm) and CPLEX + Var.Fix.
(A/ = 20,30,50,80; N = M/S ; A7; Arbitrary Costs)............. 295
B.21 Results for the UDOMP: (COV - DOMPAeRM) and Specialized Branch k,
Cut, (M = 20,30, 50, 80; N = 3,5; A7; Euclidean Distance Based Costs). . . 296
B.22 Results for the UDOMP: (COV - DOMPA£RM) and CPLEX + Var.Fix.
(A/ = 20,30,50, 80; N = fM/3]; A7; Euclidean Distance Based Costs). ... 296
B.23 Results for the UDOMP: (ALT - DOMPA ) and Variable Fixing (M = 30,
50, 80, 100; N = 3, 5; A!-A3, Arbitrary Costs).................297
B.24 Results for tlxe UDOMP: (ALT - DOMP3A6RM) and BEAMR (M = 30, 50,
80, 100, JV = 3,5; A4, Arbitrary Costs)..................... 297
B.25 Results for the UDOMP: (ALT - DOMP3A ) and Variable Fixing (M = 30,
50, 80, 100, N = 3, 5; Ax-A3, Euclidean Distance Based Costs)........298
B.26 Results for the UDOMP: (ALT - DOMPAeR«) and BEAMR (M = 30, 50,
80, 100, JV = 3,5; A4, Euclidean Distance Based Costs)............ 298
LIST OF TABLES__________________________________^_________327
B.27 Results for the UDOMP: {ALT - DOMP3AeR«) and Variable Fixing (M =
20,30, 50, 80; TV = 3,5,fM/S]; A7-A9, Arbitrary Costs)............299
B.28 Results for the UDOMP: (ALT - DOMP3AeR«) aud Variable Fixing (M =
20,30, 50, 80; TV = 3,5, [M/3]; A7-A9, Euclidean Distance Based Costs). . . 300
B.29 Results for the OTP: Algorithm 5.1 with Initial Order (M = 30, 50; TV = 3,5,
M/S , M/2; A4-A6).............................. . 301
B.30 Results for the OTP: Algorithm 5.1 with Initial Order (M = 80,100; TV =
3,5, fM/3], M/2; A4-A6)............................. 302
B.31 Results for the OTP: Algorithm 5.1 with k = 1 (M = 30,50; TV = 3, 5.
[M/31, M/2; A4-A6)............................... 303
B.32 Results for the OTP: Algorithm 5.1 with k = 1 (M = 80,100; TV = 3. 5.
rM/3], M/2; A4-A6)............................... 304
B.33 Results for the OTP: Algorithm 5.1 with k = 2 (M = 30,50; N = 3. 5.
[ M/31, M/2; A4-A6)............................... 305
B.34 Results for the OTP: Algorithm 5.1 with k = 2 (M = 80,100; TV = 3. 5.
fM/31, M/2; A4-A6)............................... 300
B.35 Results for the OTP: (MIP - OTP) and MlP-Solver of CPLEX (M =
30,50; TV = 3, 5, fM/3],M/2; A4-A6)...................... 307
B.36 Results for the OTP: (MIP - OTP) and MlP-Solver of CPLEX (M =
80,100; TV = 3,5, fM/3l, M/2; A4-As)...................... 308
B.37 Results for the OTP: (MIP - OTP) and BEAMR (M = 30,50; A = 3. 5,
I M/31, M/2; A4-A6)............................... 309
B.38 Results for the OTP: (MIP - OTP) and BEAMR (M = 80,100; N =
3,5, ( M/31, M/2; VA6)............................. 310
B.39 Results for the CDOMP: VNS Based Heuristic (M = 20, 30, 50. 80; Ar =
3,5, CM/31; A1-A3)................................ 311
B.40 Results for the CDOMP: VNS Based Heuristic (M = 20,30,50.80; TV =
3,5, CM/31; A4-A6)................................ 312
B.41 Results for the CDOMP: VNS Based Heuristic (M = 20,30,50.80; N =
3,5, CM/31; A7-A9)................................ 313
B.42 Results for the CDOMP: (CDOMP - MIP) and MlP-Solver of CPLEX
(M = 20,30, 50,80; TV = 3,5, fA//3l; AKA3)..................314
B.43 Results for the CDOMP: (CDOMP - MIP) and MlP-Solver of CPLEX
(M = 20,30, 50,80; TV = 3,5, CM/31; A4-A6)..................315
B.44 Results for the CDOMP: (CDOMP - MIP) and MlP-Solver of CPLEX
(M = 20,30,50,80; TV = 3,5, CM/31; A7-A9)..................316
328___________________________________________________________LIST OF TABLES
B.45 Results for the CDOMP: (CDOMP - MIP) and BEAMR (M = 20,30, 50,80;
N = 3,5, [A//31; Aj-Aa).............................317
B.46 Results for the CDOMP: (CDOMP - MIP) and BEAMR (Af = 20, 30,50,80;
iV = 3,5, [M/3]; A4-A6)............................. 318
B.47 Results for the CDOMP-MCO: VNS Based Heuristic and MlP-Solver of
CPLEX (Af = 20,30,; JV = 3,5, fM/31; A2-A5)................319
B.48 Results for the CDOMP-MCO: VNS Based Heuristic and MlP-Solver of
CPLEX (M = 50,80; N = 3, 5, [M/3 |; A2-A5)................. 320
B.49 Results for the CDOMP-MCO: VNS Based Heuristic and MlP-Solver of
CPLEX (M = 20,30; N = 3, 5, [M/3 |; A6-A9)................. 321
B.50 Results for the CDOMP-MCO: VNS Based Heuristic and MlP-Solver of
CPLEX (M = 50,80; N = 3,5, [Af/3]; A6-A9)................. 322
List of Figures
1.1 Example of the Fermat-Problem........................ 9
1.2 Example for a Network Location Problem................... 10
2.1 Example of the UDOMP: Optimal Solutions and Allocations......... 26
2.2 Optimal Solutions and Allocations (Customer or Client Point of View). . . 47
2.3 Optimal Solutions and Allocations (Supplier Point of View)......... 48
3.1 Relationship Between u- and u-Variables................... 69
3.2 Illustration of the Cost Radius c (fc_1) Around Location i........... 74
5.1 Example of the OTP............................... 207
6.1 Optimal Location Solution with Different Optimal Allocations........ 234
6.2 Example of the CDOMP: Optimal Location and Allocation Solution (Sup-
plier Point of View)............................... 237
6.3 Example of the CDOMP: Optimal Location and Allocation Solution (Logis-
tics Provider Point of View)........................... 240
329
List of Algorithms
2.1 Generic VNS................................... 61
3.1 Specialized Branch k Cut for (COV - DOMP* 0).............. 84
3.2 Specialized Branch Cut for (COV - DOMP^ 0).............. 108
3.3 Specialized Branch k Cut for (COV - DOMPAeR«), resp.
(COV-DOMP^,,).............................. 131
4.1 Algorithmic Framework for BEAMR...................... 186
5.1 Exchange Heuristic for the OTP......................... 216
5.2 Exact Solution Procedure for the OTP, Based on BEAMR.......... 221
5.3 TestFeasibility((i, z),LB)............................ 222
6.1 Exact Solution Procedure for the CDOMP, Based on BEAMR........ 25G
6.2 TestFeasibility(A-,(j/,2),LB).......................... 257
331
|
| any_adam_object | 1 |
| author | Velten, Sebastian |
| author_facet | Velten, Sebastian |
| author_role | aut |
| author_sort | Velten, Sebastian |
| author_variant | s v sv |
| building | Verbundindex |
| bvnumber | BV035504833 |
| classification_rvk | QH 463 QP 530 SK 970 |
| ctrlnum | (OCoLC)551645958 (DE-599)DNB992492661 |
| dewey-full | 658.50151972 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.50151972 |
| dewey-search | 658.50151972 |
| dewey-sort | 3658.50151972 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Mathematik Wirtschaftswissenschaften |
| format | Thesis Book |
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| genre | (DE-588)4113937-9 Hochschulschrift gnd-content |
| genre_facet | Hochschulschrift |
| id | DE-604.BV035504833 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T21:39:07Z |
| institution | BVB |
| isbn | 9783830042525 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-017560997 |
| oclc_num | 551645958 |
| open_access_boolean | |
| owner | DE-355 DE-BY-UBR DE-945 DE-92 DE-N2 DE-188 DE-473 DE-BY-UBG DE-634 |
| owner_facet | DE-355 DE-BY-UBR DE-945 DE-92 DE-N2 DE-188 DE-473 DE-BY-UBG DE-634 |
| physical | XII, 341 S. graph. Darst. |
| publishDate | 2009 |
| publishDateSearch | 2009 |
| publishDateSort | 2009 |
| publisher | Kovač |
| record_format | marc |
| series | Schriftenreihe Logistik-Management in Forschung und Praxis |
| series2 | Schriftenreihe Logistik-Management in Forschung und Praxis |
| spelling | Velten, Sebastian Verfasser aut Discrete location problems with flexible objectives Sebastian Velten Hamburg Kovač 2009 XII, 341 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Schriftenreihe Logistik-Management in Forschung und Praxis 23 Zugl.: Saarbrücken, Univ., Diss., 2008 Algorithmus stw Betriebliche Standortwahl stw Diskrete Entscheidung stw Heuristisches Verfahren stw Mathematische Optimierung stw Operations Research - Standorttheorie - Lineare Optimierung - Logistik Transportproblem stw Lineare Optimierung (DE-588)4035816-1 gnd rswk-swf Standortproblem (DE-588)4301515-3 gnd rswk-swf Operations Research (DE-588)4043586-6 gnd rswk-swf Entscheidung bei mehrfacher Zielsetzung (DE-588)4113444-8 gnd rswk-swf Standorttheorie (DE-588)4121720-2 gnd rswk-swf Logistik (DE-588)4036210-3 gnd rswk-swf Diskrete Entscheidung (DE-588)4194151-2 gnd rswk-swf Flexible Planung (DE-588)4154617-9 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Operations Research (DE-588)4043586-6 s Standorttheorie (DE-588)4121720-2 s Lineare Optimierung (DE-588)4035816-1 s Logistik (DE-588)4036210-3 s DE-604 Standortproblem (DE-588)4301515-3 s Diskrete Entscheidung (DE-588)4194151-2 s Entscheidung bei mehrfacher Zielsetzung (DE-588)4113444-8 s Flexible Planung (DE-588)4154617-9 s DE-188 Schriftenreihe Logistik-Management in Forschung und Praxis 23 (DE-604)BV019839984 23 text/html http://www.verlagdrkovac.de/978-3-8300-4252-5.htm Ausführliche Beschreibung HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017560997&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Velten, Sebastian Discrete location problems with flexible objectives Schriftenreihe Logistik-Management in Forschung und Praxis Algorithmus stw Betriebliche Standortwahl stw Diskrete Entscheidung stw Heuristisches Verfahren stw Mathematische Optimierung stw Operations Research - Standorttheorie - Lineare Optimierung - Logistik Transportproblem stw Lineare Optimierung (DE-588)4035816-1 gnd Standortproblem (DE-588)4301515-3 gnd Operations Research (DE-588)4043586-6 gnd Entscheidung bei mehrfacher Zielsetzung (DE-588)4113444-8 gnd Standorttheorie (DE-588)4121720-2 gnd Logistik (DE-588)4036210-3 gnd Diskrete Entscheidung (DE-588)4194151-2 gnd Flexible Planung (DE-588)4154617-9 gnd |
| subject_GND | (DE-588)4035816-1 (DE-588)4301515-3 (DE-588)4043586-6 (DE-588)4113444-8 (DE-588)4121720-2 (DE-588)4036210-3 (DE-588)4194151-2 (DE-588)4154617-9 (DE-588)4113937-9 |
| title | Discrete location problems with flexible objectives |
| title_auth | Discrete location problems with flexible objectives |
| title_exact_search | Discrete location problems with flexible objectives |
| title_full | Discrete location problems with flexible objectives Sebastian Velten |
| title_fullStr | Discrete location problems with flexible objectives Sebastian Velten |
| title_full_unstemmed | Discrete location problems with flexible objectives Sebastian Velten |
| title_short | Discrete location problems with flexible objectives |
| title_sort | discrete location problems with flexible objectives |
| topic | Algorithmus stw Betriebliche Standortwahl stw Diskrete Entscheidung stw Heuristisches Verfahren stw Mathematische Optimierung stw Operations Research - Standorttheorie - Lineare Optimierung - Logistik Transportproblem stw Lineare Optimierung (DE-588)4035816-1 gnd Standortproblem (DE-588)4301515-3 gnd Operations Research (DE-588)4043586-6 gnd Entscheidung bei mehrfacher Zielsetzung (DE-588)4113444-8 gnd Standorttheorie (DE-588)4121720-2 gnd Logistik (DE-588)4036210-3 gnd Diskrete Entscheidung (DE-588)4194151-2 gnd Flexible Planung (DE-588)4154617-9 gnd |
| topic_facet | Algorithmus Betriebliche Standortwahl Diskrete Entscheidung Heuristisches Verfahren Mathematische Optimierung Operations Research - Standorttheorie - Lineare Optimierung - Logistik Transportproblem Lineare Optimierung Standortproblem Operations Research Entscheidung bei mehrfacher Zielsetzung Standorttheorie Logistik Flexible Planung Hochschulschrift |
| url | http://www.verlagdrkovac.de/978-3-8300-4252-5.htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017560997&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV019839984 |
| work_keys_str_mv | AT veltensebastian discretelocationproblemswithflexibleobjectives |