Zanjirani Farahani / Hekmatfar Facility Location

Concepts, Models, Algorithms and Case Studies
1. Auflage 2009
ISBN: 978-3-7908-2151-2
Verlag: Physica-Verlag HD
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 549 Seiten

Reihe: Contributions to Management Science

This book deals with location problems. Location problems establish a set of facilities (resources) to minimize the cost of satisfying a set of demands (customers) with respect to a set of constraints. There are four components that describe location problems: customers, who are assumed to be already located at points or on routes, facilities that will be located, a space in which customers and facilities are located, and a metric that indicates geographical and chronological distances between customers and facilities. This book describes these parts in each specific location model. Location models are used in a variety of applications such as locating warehouses within a supply chain to minimize the average time to market, locating noxious material to maximize its distance to the public, etc. In this book, readers can find these applications exemplified by real-world cases for each particular model. The relationship between location problems and other areas such as supply chains is also considered here.

Autoren/Hrsg.

Zanjirani Farahani, Reza

Hekmatfar, Masoud

Inhaltsverzeichnis

1;Contents;6
2;Introduction;8
2.1;References;11
3;1 Distance Functions in Location Problems;12
3.1;1.1 Distance and Norms Specifications;13
3.2;1.2 Distances Function;13
3.3;1.3 Different Kinds of Distances;15
3.3.1;1.3.1 Aisle Distance;15
3.3.2;1.3.2 Distance Matrix;15
3.3.3;1.3.3 Minimum Lengths Path;16
3.3.4;1.3.4 Block Distance;16
3.3.5;1.3.5 Gauges Measures;17
3.3.6;1.3.6 Variance of Distances;18
3.3.7;1.3.7 Hilbert Curve;18
3.3.8;1.3.8 Mahalanobis Distance;19
3.3.9;1.3.9 Hamming Distance;19
3.3.10;1.3.10 Levenshtein Distance;19
3.3.11;1.3.11 Hausdorff Distance;20
3.4;1.4 Summary;23
3.5;References;23
4;2 An Overview of Complexity Theory;25
4.1;2.1 Advantage of Complexity Theory;26
4.1.1;2.1.1 Computational Complexity;26
4.2;2.2 Abstract Models of Computation: Abstract Machines;26
4.2.1;2.2.1 Preliminary Definitions;26
4.2.2;2.2.2 Turing Machine Models;27
4.3;2.3 Big-O Notation (Wood 1987);28
4.3.1;2.3.1 Example;29
4.4;2.4 Time Complexity;30
4.4.1;2.4.1 Constant Time;30
4.4.2;2.4.2 Linear Time (Sipser 1996);30
4.4.3;2.4.3 Polynomial Time (Papadimitriou 1994);30
4.4.4;2.4.4 Exponential Time (Sipser 1996);31
4.5;2.5 Decision Problems;31
4.6;2.6 Reduction;31
4.6.1;2.6.1 Linear Reduction;32
4.6.2;2.6.2 Polynomial Reduction;32
4.6.3;2.6.3 Polynomial Reduction: Many-One Polynomially Reducible;32
4.7;2.7 Examples;32
4.7.1;2.7.1 Traveling Salesman Optimization Problem;33
4.7.2;2.7.2 Satisfiability Problem;33
4.7.3;2.7.3 Hamiltonian Cycle Problem;34
4.7.4;2.7.4 Clique Problem;34
4.8;2.8 Complexity Classes;34
4.8.1;2.8.1 Class P;34
4.8.2;2.8.2 Class NP;35
4.8.3;2.8.3 Class NP-Complete;37
4.8.4;2.8.4 Class NP-Hard;40
4.9;2.9 Further Reading;41
4.10;References;41
5;3 Single Facility Location Problem;43
5.1;3.1 Problem Formulation;44
5.1.1;3.1.1 A General Formulation of the Problem;44
5.1.2;3.1.2 Rectilinear Distance with Point Facilities;45
5.1.3;3.1.3 Square Euclidean Distance with Point Facilities;46
5.1.4;3.1.4 Euclidean Distance with Point Facilities;46
5.1.5;3.1.5 LP-Norm Distance with Point Facilities;46
5.1.6;3.1.6 Regional Facilities Problem (Drezner 1986);47
5.2;3.2 Solution Techniques;48
5.2.1;3.2.1 Techniques for Discrete Space Location Problems;48
5.2.2;(Heragu 1997);48
5.2.3;3.2.2 Techniques for Continues Space Location Problems;50
5.3;3.3 Case Study (Heragu 1997);72
5.4;References;74
6;4 Multifacility Location Problem;75
6.1;4.1 Applications and Classifications;75
6.2;4.2 Models;76
6.2.1;4.2.1 MiniSum;76
6.2.2;4.2.2 MiniMax;81
6.2.3;4.2.3 Other Models;83
6.3;4.3 Solution Techniques;87
6.3.1;4.3.1 MiniSum;87
6.3.2;4.3.2 MiniMax;94
6.3.3;4.3.3 Solution Techniques for other Models;95
6.3.4;4.3.4 Some Heuristic and Metaheuristic Methods;95
6.4;4.4 Case Study;96
6.5;References;96
7;5 Location Allocation Problem;99
7.1;5.1 Classification of Location-Allocation Problem;99
7.1.1;5.1.1 Classifications of Facilities;100
7.1.2;5.1.2 Classified on the Physical Space or Locations;100
7.1.3;5.1.3 Classifications of the Demand;100
7.2;5.2 Models;101
7.2.1;5.2.1 General LA Model (Cooper 1963);101
7.2.2;5.2.2 LA Model Each Customer Covered by Only One Facility;102
7.2.3;5.2.3 LA Model with FacilityÌs Opening Cost;103
7.2.4;5.2.4 Capacitated LA Model with Stochastic Demands;104
7.2.5;(Zhou and Liu 2003);104
7.3;5.3 Solution Techniques;105
7.3.1;5.3.1 Exact Solutions (Cooper 1963);106
7.3.2;5.3.2 Heuristic Methods;107
7.4;Procedure 1;110
7.5;Procedure 2;111
7.5.1;5.3.3 Metaheuristic Methods (Salhi and Gamal 2003);111
7.6;5.4 Case Study;111
7.6.1;5.4.1 A Facility Location Allocation Model for Reusing Carpet;112
7.6.2;Materials (Louwers et al. 1999);112
7.6.3;5.4.2 A New Organ Transplantation Location-Allocation Policy;113
7.6.4;(Bruni et al. 2006);113
7.7;References;114
8;6 Quadratic Assignment Problem;116
8.1;6.1 Formulations of QAP;119
8.1.1;6.1.1 Integer Programming Formulations (ILP);119
8.1.2;6.1.2 Mixed Integer Programming Formulations (MILP);121
8.1.3;6.1.3 Formulation by Permutations;123
8.1.4;6.1.4 Trace Formulation;124
8.1.5;6.1.5 Graph Formulation;124
8.2;6.2 QAP Related Problems;125
8.2.1;6.2.1 The Quadratic Bottleneck Assignment Problem (QBAP);125
8.2.2;6.2.2 The Biquadratic Assignment Problem (BiQAP);125
8.2.3;6.2.3 The Quadratic Semi-Assignment Problem (QSAP);126
8.2.4;6.2.4 The Multiobjective QAP (MQAP);126
8.2.5;6.2.5 The Quadratic Three-Dimensional Assignment Problem;127
8.2.6;(Q3AP);127
8.2.7;6.2.6 The Generalized Quadratic Assignment Problem (GQAP);128
8.2.8;6.2.7 Stochastic QAP (SQAP);129
8.3;6.3 Solution Techniques;130
8.3.1;6.3.1 Computational Complexity;130
8.3.2;6.3.2 Lower Bounds;130
8.3.3;6.3.3 Exact Algorithms;133
8.3.4;6.3.4 Heuristic Algorithms;134
8.3.5;6.3.5 Metaheuristic Algorithms;135
8.3.6;6.3.6 Comparing QAP Algorithms;139
8.4;6.4 Case Study;140
8.4.1;6.4.1 Hospital Layout as a Quadratic Assignment Problem;140
8.4.2;(Elshafei 1977);140
8.4.3;6.4.2 Backboard Wiring Problem (Steinberg 1961);141
8.4.4;6.4.3 Minimizing WIP Inventories (Benjaafar 2002);141
8.4.5;6.4.4 Zoning in Forest (Bos 1993);142
8.4.6;6.4.5 Computer Motherboard Design Problem (Miranda 2005);142
8.5;References;142
9;7 Covering Problem;149
9.1;7.1 Problem Formulation;150
9.2;7.2 Total Covering Problem;151
9.2.1;7.2.1 Maximizing the Number of Points Covered More than Once;153
9.2.2;7.2.2 Multiple Total Covering Problems (Mirchandani et al. 1990);153
9.2.3;7.2.3 Total Covering Problem with the Preference of Selecting;154
9.2.4;Location of Existing Facilities (Daskin 1995);154
9.2.5;7.2.4 Total Edge Covering Problem (Daskin 1995);155
9.2.6;7.2.5 Notes on Total Covering Problems;157
9.3;7.3 Partial Covering Problem;159
9.3.1;7.3.1 Minimizing Costs Arisen from Not Covering Demand Points;160
9.3.2;(Mirchandani and Francis 1990);160
9.3.3;7.3.2 Minimizing Costs of Locating Facilities and Costs Arisen;160
9.3.4;from Not Covering Demand Points;160
9.3.5;7.3.3 Maximum Covering Location Problems (Berman;161
9.3.6;et al. 2003);161
9.3.7;7.3.4 Expected Maximum Covering Problem (Daskin 1995);162
9.3.8;7.3.5 Maximum Covering Problem Considering Non-Ascending;164
9.3.9;Coverage Function (Berman et al. 2003);164
9.4;7.4 The Bi-Objective Covering Tour Problem (Jozefowieza;166
9.5;et al. 2007);166
9.6;7.5 A Fuzzy Multi Objective Covering Based Vehicle Location;167
9.7;Model for Emergency Services (Araz et al. 2007);167
9.8;7.6 Solving Methods;169
9.8.1;7.6.1 Exact Methods;169
9.8.2;7.6.2 Heuristic Methods;176
9.8.3;7.6.3 Metaheuristic Methods;177
9.9;7.7 Case Study;177
9.9.1;7.7.1 Combination of MCDM and Covering Techniques;177
9.9.2;(Farahani and Asgari 2007);177
9.10;References;180
10;8 Median Location Problem;181
10.1;8.1 Classification;182
10.1.1;8.1.1 1-Median;182
10.1.2;8.1.2 P-Median;182
10.1.3;8.1.3 An Example;182
10.2;8.2 Mathematical Models;183
10.2.1;8.2.1 Classic Model;183
10.2.2;8.2.2 Capacitated Plant Location Problem Model (CPLPM);184
10.2.3;8.2.3 Capacitated P-median Problem (Lorenaa 2004);186
10.3;8.3 Solution Techniques;187
10.3.1;8.3.1 Lemma;188
10.3.2;8.3.2 Solving 1-Median Problem Algorithm on Tree;188
10.3.3;(Goldman 1971);188
10.3.4;8.3.3 Exact Methods;189
10.3.5;8.3.4 Heuristic Algorithms;189
10.3.6;8.3.5 Metaheuristic Algorithms;190
10.4;8.4 Comparison of Methods;191
10.5;8.5 Studying Statically the Methods for Solutions of Median;191
10.6;Problem (Reese 2005);191
10.6.1;8.5.1 Classification of Solving Methods by Period;192
10.6.2;8.5.2 Classification of Different Solving Methods;192
10.7;8.6 Case Study;192
10.7.1;8.6.1 Post Center Locations (Alba and Dominquez 2006);192
10.7.2;8.6.2 Entrance Exam Facilities (Correa et al. 2004);193
10.7.3;8.6.3 Polling Station Location (Ghiani et al. 2002);193
10.8;References;194
11;9 Center Problem;196
11.1;9.1 Applications and Classifications;197
11.1.1;9.1.1 K-Network P-Center Problem;198
11.1.2;9.1.2;198
11.1.3;Facility;198
11.1.4;-Centdian Problem;198
11.1.5;9.1.3;198
11.1.6;Centrum Multi-Facility Problem;198
11.1.7;9.1.4 P-Center Problem with Pos/Neg Weights;199
11.1.8;9.1.5 Anti P-Center Problem;199
11.1.9;9.1.6 Continuous P-Center Problem;199
11.1.10;9.1.7 Asymmetric P-Center Problem;199
11.2;9.2 Models;199
11.2.1;9.2.1 Vertex P-Center Problem;199
11.2.2;9.2.2 Vertex P-Center Problem with Demand-Weighted Distance;201
11.2.3;9.2.3 Capacitated Vertex P-Center Problem;201
11.3;9.3 Exact Solution Approaches;202
11.3.1;9.3.1 Center Problems on a Tree Network;202
11.3.2;9.3.2 Center Problems on a General Graph;210
11.4;9.4 Approximate Solution Approaches;217
11.5;9.5 Case Study;218
11.5.1;9.5.1 A Health Resource Case (Pacheco and Casado 2005);218
11.6;References;219
12;10 Hierarchical Location Problem;221
12.1;10.1 Applications and Classifications;222
12.2;10.2 Flow-Based Hierarchical Location Problem;224
12.2.1;10.2.1 Flow-Based Formulation for Single-Flow Systems (S ahin;224
12.2.2;and S ural 2007);224
12.2.3;10.2.2 Flow-Based Formulation for Multi-Flow Systems (S ahin;226
12.2.4;and S ural 2007);226
12.3;10.3 Median-Based Hierarchical Location Problem;227
12.4;(Daskin 1995);227
12.4.1;10.3.1 Median-Based Formulation for Globally Inclusive Service;227
12.4.2;Hierarchies;227
12.4.3;10.3.2 Median-Based Formulation for Locally Inclusive Service;229
12.4.4;Hierarchies;229
12.4.5;10.3.3 Median-Based Formulation for Successively Exclusive;230
12.4.6;Service Hierarchies;230
12.5;10.4 Coverage-Based Hierarchical Location Problem;230
12.6;(Daskin 1995);230
12.6.1;10.4.1 Hierarchical Maximal Covering Location Problem;231
12.6.2;10.4.2 Hierarchical Maximal Covering Location Problem;232
12.6.3;with Covering all Kinds of Demands;232
12.7;10.5 Median-Based Hierarchical Relocation Problem (Teixeira;234
12.8;and Antunes 2008);234
12.8.1;10.5.1 Median-Based Hierarchical Relocation Problem;234
12.8.2;with Closest Assignment;234
12.8.3;10.5.2 Median-Based Hierarchical Relocation Problem with Path;236
12.8.4;Assignment;236
12.9;10.6 Solving Algorithms for Hierarchical Location Problem;237
12.10;10.7 Case Study;240
12.10.1;10.7.1 A Hierarchical Model for the Location of Maternity;240
12.10.2;Facilities in the Municipality of Rio de Janeiro;240
12.10.3;(Galv Ú ao et al. 2002 and 2006);240
12.10.4;10.7.2 Locational Analysis for Regionalization of Turkish Red;240
12.10.5;Crescent Blood Services (S ahin et al. 2007);240
12.10.6;10.7.3 School Network Planning in Coimbra, Portugal (Teixeira;241
12.10.7;and Antunes 2008);241
12.11;References;241
13;11 Hub Location Problem;244
13.1;11.1 Applications and Classifications;246
13.2;11.2 Models;248
13.2.1;11.2.1 Single Hub Location Problem (OÌKelly 1987);248
13.2.2;11.2.2 P-Hub Location Problem (OÌKelly 1987);250
13.2.3;11.2.3 Multiple Allocation P-Hub Location Model (P-Hub;252
13.2.4;Median Location Model) (Campbell 1991);252
13.2.5;11.2.4 P-Hub Median Location Problem with Fixed Costs;253
13.2.6;(OÌ Kelly 1992);253
13.2.7;11.2.5 Single Spoke Assignment P-Hub Median Location;254
13.2.8;Problem (Single Allocation P-Hub Location Problem);254
13.2.9;(Daskin 1995);254
13.2.10;11.2.6 The Extension Model of Fixed Cost for Connecting;256
13.2.11;a Spoke to a Hub (Campbell 1994);256
13.2.12;11.2.7 Minimum Value Flow on any Spoke/Hub Connection;257
13.2.13;Problem (Campbell 1994);257
13.2.14;11.2.8 Capacity Limitation of Hub Location Problem;258
13.2.15;(Campbell 1994);258
13.2.16;11.2.9 P-Hub Center Location Problem (Campbell 1994);259
13.2.17;11.2.10 Hub Covering Location Problem (Campbell 1994);260
13.3;11.3 Solution Techniques;262
13.3.1;11.3.1 Various Kinds of Algorithms;262
13.3.2;11.3.2 Some Relevant Algorithms;266
13.4;11.4 Case Study;267
13.4.1;11.4.1 The Policy of Open Skies in the Middle East;268
13.4.2;(Adler and Hashai 2005);268
13.4.3;11.4.2 A Hub Port in the East Coast of South America (Aversa;268
13.4.4;et al. 2005);268
13.4.5;11.4.3 A Hub Model in Brunswick, Canada (Eiselt 2007);268
13.4.6;11.4.4 A Hub/Spoke Network in Brazil (Cunha and Silva 2007);269
13.5;References;269
14;12 Competitive Location Problem;272
14.1;12.1 Applications and Classifications;272
14.1.1;12.1.1 Game Theories (Winston and Wayne 1995);275
14.1.2;12.1.2 Static Competition;277
14.1.3;12.1.3 Competition with Foresight;277
14.1.4;12.1.4 Dynamic Models and Competitive Equilibrium;277
14.1.5;12.1.5 Point vs. Regional Demand;278
14.1.6;12.1.6 Patronizing Behavior;278
14.1.7;12.1.7 Attraction Function;279
14.1.8;12.1.8 Decision Space;280
14.2;12.2 Models;281
14.2.1;12.2.1 Gravity Problem;281
14.2.2;12.2.2 The Maximum Capture Problem Model (MAXCAP);284
14.2.3;(Serra and ReVelle 1995);284
14.2.4;12.2.3 The Maximum Capture Problem with Price Model;286
14.2.5;(PMAXCAP) (Serra and ReVelle 1998);286
14.2.6;12.2.4 Flow Capturing Location Allocation Problem Model;289
14.2.7;(FCLAP);289
14.3;12.3 Case Study;292
14.3.1;12.3.1 A Case in Toronto (Aboolian et al. 2006);292
14.3.2;12.3.2 A Case in Yuanlin Taiwan (Wu and Lin 2003);293
14.4;References;294
15;13 Warehouse Location Problem;296
15.1;13.1 Classifications;297
15.2;13.2 Models;298
15.2.1;13.2.1 Warehouse Location Problem without Fixed;298
15.2.2;Installation Costs (William et al. 1958);298
15.2.3;13.2.2 Warehouse Location Problem with Fixed Cost;300
15.2.4;of Establishment (Akinc and Khumawala 1977);300
15.2.5;13.2.3 Capacitated Warehouse Location Problem with;302
15.2.6;Constraints in Customers Being Serviced (Nagy 2004);302
15.2.7;13.2.4 Single Stage Capacitated Warehouse Location Model;303
15.2.8;(Sharma and Berry 2007);303
15.2.9;13.2.5 Redesigning a Warehouse Network (Melachrinoudis;306
15.2.10;and Min 2007);306
15.3;13.3 Solution Methods;310
15.3.1;13.3.1 Exact Solution Methods;310
15.3.2;13.3.2 Heuristic and Metaheuristic Methods;311
15.4;13.4 Case Study;313
15.4.1;13.4.1 Redesigning a Warehouse Network;313
15.4.2;(Melachrinoudis and Min 2007);313
15.4.3;13.4.2 Warehouse Location Problems for Air Freight Forwarders;313
15.4.4;(Wan et al. 1998);313
15.5;References;314
16;14 Obnoxious Facility Location;316
16.1;14.1 Applications and Classifications;317
16.1.1;14.1.1 Applications;317
16.1.2;14.1.2 Revolution of Undesirable Facility Problem;317
16.1.3;14.1.3 Classification of Undesirable Facility Problems;319
16.2;14.2 Models;320
16.2.1;14.2.1 Dispersion Problem (Daskin 1995);320
16.2.2;14.2.2 Undesirable Facility Location Problem (Daskin 1995);321
16.2.3;14.2.3 Hazardous Materials Routing Problem;324
16.2.4;14.2.4 Obnoxious Facilities Location-Routing Problem;332
16.2.5;14.2.5 Multiobjective Obnoxious Facilities Location Problem;338
16.2.6;(Rakas et al. 2004);338
16.3;14.3 Solutions and Techniques;340
16.4;14.4 Case Study;342
16.4.1;14.4.1 Obnoxious Facility Location and Routing in Anatolian;342
16.4.2;Region of Turkey (Alumur and Kara 2007);342
16.4.3;14.4.2 Designing Emergency Response Network for Hazardous;343
16.4.4;Materials Transportation (Berman et al. 2007);343
16.4.5;14.4.3 Locating Waste Pipelines to Minimize their Impact;343
16.4.6;on Marine Environment (Ceceres et al. 2007);343
16.5;References;344
17;15 Dynamic Facility Location Problem;347
17.1;15.1 Classifications;348
17.2;15.2 Mathematical Formulations;349
17.2.1;15.2.1 Static Model (Wesolowsky 1973);349
17.2.2;15.2.2 Dynamic P-Median Model (Owen and Daskin 1998);350
17.2.3;15.2.3 Multiperiod Model (Wesolowsky and Truscott 1975);352
17.2.4;15.2.4 Probabilistic Model (Rosental et al. 1978);353
17.3;15.3 Solution Techniques;354
17.3.1;15.3.1 Fundamental Lemmas;355
17.3.2;15.3.2 Single Relocation at Discrete Time;356
17.3.3;15.3.3 Multiple Relocations at Discrete Times;357
17.3.4;Without Relocation Costs (Z.-Farahani et al. 2009);357
17.3.5;15.3.4 Multiple Relocations at Discrete Times;358
17.3.6;with Relocation Costs;358
17.3.7;15.3.5 Complete Enumeration;359
17.3.8;15.3.6 Non-Duplicating Enumeration;359
17.3.9;15.3.7 Incomplete DP;360
17.3.10;15.3.8 An Especial BIP;360
17.3.11;15.3.9 Relocation at Continues Times;364
17.3.12;15.3.10 Iterative Algorithm for Obtaining Optimal Solution;367
17.3.13;15.3.11 Static Stochastic Techniques;368
17.4;15.4 Case Study;369
17.4.1;15.4.1 A Dynamic Model for School Network Planning (Antunes;370
17.4.2;and Peeters 2000);370
17.4.3;15.4.2 A Multiperiod Set Covering for Dynamic Redeployment;370
17.4.4;of Ambulances (Rajagopalan et al. 2008);370
17.4.5;15.4.3 A Multi-period Model for Combat Logistics (Gue 2003);371
17.5;References;372
18;16 Multi-Criteria Location Problem;373
18.1;16.1 Applications and Classifications;374
18.2;16.2 Models;375
18.2.1;16.2.1 Private and Public Facilities;375
18.2.2;16.2.2 Balancing Objective Functions;376
18.2.3;16.2.3 Pull, Push and PullÒPush Objectives;377
18.2.4;16.2.4 Mathematical Models;379
18.3;16.3 Solution Techniques;383
18.3.1;16.3.1 The MCDM Techniques;383
18.3.2;16.3.2 Metaheuristics for the MODM;385
18.3.3;16.3.3 Multi-Objective Combinatorial Optimization;385
18.4;16.4 Case Study;386
18.4.1;16.4.1 LRP (Lin and kwok 2006);386
18.4.2;16.4.2 Facility Layout (Chiang et al. 2006);387
18.4.3;16.4.3 Fire Station Locations;388
18.4.4;16.4.4 The 2-Facility Centdian Network Problem (Perez-Brito;389
18.4.5;et al. 1998);389
18.4.6;16.4.5 Military Logistics (Z-Farahani and Asgari 2007);390
18.4.7;16.4.6 A Paper Recycling System (Pati et al. 2008);390
18.5;References;391
19;17 Location-Routing Problem;394
19.1;17.1 An Introduction to VRP;394
19.1.1;17.1.1 Definition of VRP;394
19.1.2;17.1.2 The Traveling Salesman Problem;397
19.1.3;17.1.3 A Classification of Capacitated VRP;397
19.2;17.2 LRP;398
19.2.1;17.2.1 Applications of LRP;400
19.2.2;17.2.2 Classifications of LRP;401
19.3;17.3 Models;405
19.3.1;17.3.1 Classifications;405
19.3.2;17.3.2 Mathematical Models;406
19.4;17.4 Solution Techniques;411
19.4.1;17.4.1 Heuristic Methods;411
19.4.2;17.4.2 Metaheuristic Methods;412
19.5;17.5 Case Study;412
19.5.1;17.5.1 Bill Delivery Services (Lin et al. 2002);412
19.5.2;17.5.2 Contaminated Waste Disposal (Caballero et al. 2007);413
19.5.3;17.5.3 Logistics System (Lin and Kwok 2006);414
19.6;References;414
20;18 Storage System Layout;417
20.1;18.1 Assumptions and Classifications;418
20.2;18.2 Storage Location Assignment Problem Based on Product;421
20.3;Information;421
20.3.1;18.2.1 Dedicated Storage Location Policy;421
20.3.2;18.2.2 Cube-Per-Order Index (COI);427
20.3.3;18.2.3 Class-Based Storage Location Policy;427
20.3.4;18.2.4 Class-Based Dedicated Storage Location Policy (COI);429
20.3.5;18.2.5 Full Turn-over Based Storage;431
20.4;18.3 Storage Location Assignment Problem;434
20.5;Based on Item Information (SLAP/II);434
20.5.1;18.3.1 Assignment Problem and Vector Assignment Problem;434
20.5.2;18.3.2 Shared Storage Policies;435
20.5.3;18.3.3 Duration-of-Stay Storage Policy;436
20.5.4;18.3.4 Shared Storage Policies for Unbalanced Input and Output;438
20.5.5;18.3.5 Static Shared Storage Policies;439
20.5.6;18.3.6 Adaptive Shared Storage Policies;439
20.6;18.4 Storage Location Assignment Problem;442
20.7;Based on No Information (SAP/NI);442
20.7.1;18.4.1 Randomized Storage Location Policy;442
20.8;18.5 Comparing Storage Policies;444
20.9;18.6 Family Grouping;444
20.10;18.7 Continuous Warehouse Layout;445
20.10.1;18.7.1 Storage Region Configuration;446
20.11;18.8 Dynamic Storage Location Assignment Problems;446
20.12;(Gu 2005);446
20.13;18.9 Case Study;446
20.14;References;447
21;19 Location-Inventory Problem;449
21.1;19.1 Applications and Classifications;451
21.2;19.2 Models;453
21.2.1;19.2.1 Model of Shen et al. (2003);453
21.2.2;19.2.2 Model of Nozick and Turnquist (1998);455
21.2.3;19.2.3 Model of Erlebacher and Meller (2000);456
21.2.4;19.2.4 Model of Daskin et al. (2002);458
21.2.5;19.2.5 Model of Shen and Qi (2007);461
21.2.6;19.2.6 Model of Miranda and Garrido (2008);463
21.3;19.3 Solution Approaches;465
21.3.1;19.3.1 Solution Approach of Erlebacher and Meller (2000);465
21.3.2;19.3.2 Solution Approach of Daskin et al. (2002);466
21.3.3;19.3.3 Solution Approach of Shen and Qi (2007);466
21.3.4;19.3.4 Solution Approach of Miranda and Garrido (2006);467
21.3.5;19.3.5 Solution Approach of Miranda and Garrido (2008);467
21.4;19.4 Case Study;467
21.4.1;19.4.1 Distribution System for Finished Automobiles in US;468
21.4.2;(Nozick and Turnquist 1998);468
21.5;References;468
22;20 Facility Location in Supply Chain;470
22.1;20.1 Design Phases in Supply Chain;470
22.2;20.2 Network Design in Supply Chain;471
22.2.1;20.2.1 The Role of Network Design in the Supply Chain;471
22.2.2;20.2.2 Factors Influencing Network Design Decisions;472
22.3;20.3 ClassicalModels;472
22.3.1;20.3.1 Fixed Charge Facility Location Problem (Daskin;473
22.3.2;et al. 2005);473
22.3.3;20.3.2 Uncapacitated Facility Location Model with Single;474
22.3.4;Sourcing;474
22.3.5;20.3.3 Capacitated Facility Location Model;474
22.3.6;20.3.4 Locating Plants and Distribution Centers with Multiple;476
22.3.7;Commodity;476
22.4;20.4 Integrated Decision Making Models;477
22.4.1;20.4.1 Integrated Location-Routing Models (LR);477
22.4.2;20.4.2 Integrated Inventory-Routing Models (IR);478
22.4.3;20.4.3 Integrated Location-Inventory Models (LI);478
22.5;20.5 Basic Model Formulation;479
22.5.1;20.5.1 Model Inputs;479
22.5.2;20.5.2 Model Outputs (Decision Variables);480
22.5.3;20.5.3 Objective Function and its Constraints;480
22.6;20.6 Model with Routing Cost Estimation;480
22.7;20.7 Model with Capacitated DCs;481
22.8;20.8 Model with Multiple Levels of Capacity (Amiri 2006);482
22.8.1;20.8.1 Model Inputs;482
22.8.2;20.8.2 Model Outputs (Decision Variables);483
22.8.3;20.8.3 Objective Function and its Constraints;483
22.9;20.9 Model with Service Considerations;483
22.10;20.10 Profit Maximizing Model with Demand Choice Flexibility;485
22.11;20.11 Model with Multiple Commodities;487
22.12;20.12 Model with Unreliable Supply;488
22.12.1;20.12.1 Model Inputs;489
22.12.2;20.12.2 Model Outputs (Decision Variables);489
22.12.3;20.12.3 Objective Function and its Constraints;489
22.13;20.13 Model with Facility Failures (Snyder 2003);490
22.13.1;20.13.1 Objective Function and its Constraints;491
22.14;20.14 Planning Under Uncertainty (Snyder et al. 2007);492
22.14.1;20.14.1 Model Inputs;493
22.14.2;20.14.2 Model Outputs (Decision Variables);493
22.14.3;20.14.3 Objective Function and its Constraints;493
22.15;20.15 Solution Techniques;494
22.16;20.16 Case Study;496
22.16.1;20.16.1 An Industrial Case in Supply Chain Design;496
22.16.2;and Multilevel Planning in US (Sousa et al. 2008);496
22.16.3;20.16.2 Multi-Objective Optimization of Supply Chain Networks;498
22.16.4;in Turkey (Altiparmak et al. 2006);498
22.17;References;498
23;21 Classification of Location Models and Location Softwares;502
23.1;21.1 Classification of Location Models;502
23.1.1;21.1.1 Taxonomy vs. Classification Scheme;502
23.1.2;21.1.2 Taxonomy;503
23.1.3;21.1.3 Classification Schemes;508
23.2;21.2 Facility Location Softwares;510
23.2.1;21.2.1 LoLA;512
23.2.2;21.2.2 SITATION;513
23.2.3;21.2.3 S-Distance;516
23.2.4;21.2.4 Other Facility Location Softwares;517
23.3;References;517
24;22 Demand Point Aggregation Analysis for Location Models;519
24.1;22.1 Applications;520
24.1.1;22.1.1;520
24.1.2;Median;520
24.1.3;Problem;520
24.1.4;22.1.2;520
24.1.5;Center;520
24.1.6;Problem;520
24.1.7;22.1.3 Covering Problem;521
24.2;22.2 Aggregation Errors;521
24.2.1;22.2.1 Spatial Aggregation Demand;521
24.2.2;22.2.2 Methods for Reducing Aggregation Errors;523
24.3;22.3 Computational Approach;528
24.4;References;529
25;Appendix: Metaheuristic Methods;531
25.1;Genetic Algorithm;531
25.1.1;The Simple Genetic Algorithm;532
25.2;Tabu Search;533
25.2.1;Two Important Concepts;533
25.2.2;A Simple Tabu Search Algorithm;534
25.3;Ant Colony Optimization;534
25.4;Simulated Annealing;535
25.5;Neural Networks;536
25.6;References;537
26;Index;540