Contents

Preface 203

Acknowledgements 203

Introduction 209

What is Open Design? 209

Open Design's structuring of a design problem 210

Structure of the book 213

I Exercises 215

1 Linear Programming with Negotiable Constraints 217

1.1 Linear Programming using What's Best! 218

1.2 The project developer's problem 219

1.3 The municipality's problem 222

1.4 The facility manager's problem 223

1.5 LP and multi-criteria optimisation 225

1.6 Conclusions 229

2 Monte Carlo simulation for real estate and infrastructure investments 231

2.1 Risk assessment example: single project 234

2.2 Risk diversification example: two projects 236

2.3 Monte Carlo simulation of a portfolio of real estate investments 238

2.4 Risk diversification example: portfolio of projects 240

2.5 Conclusions 243

3 Project Network Planning and Risk Assessment 245

3.1 Deterministic network planning: CPM 246

3.2 Probabilistic network planning: PERT 249

3.3 Risk assessment in network planning through Monte Carlo simulation 251

3.4 The concept of path ranking 252

3.5 Numerical examples 253

3.6 Allowance for mitigations in probabilistic network planning 258

3.7 Allowing for limited human resources 260

3.8 Conclusions 262

4 Regression analysis of construction projects from the past 263

4.1 Linear, single variable, regression analysis 263

4.2 Multiple variable regression analysis 272

4.3 Regression analysis as input for Monte Carlo simulation 277

4.4 The use of multiple variable linear regression analysis in architectural design 278

4.5 The concept of architectural repertoire 278

4.6 Ethical considerations 279

4.7 Conclusions 280

5 Preference Measurement: The key to incorporating soft variables 281

5.1 Scaling of preferences 281

5.2 Assessment of the order of preference through trade-offs and weight factors 282

5.3 Single criterion preference measurement of a group 284

5.4 Criteria ranking on relevance by a group 285

5.5 Conclusions 287

6 Integrating LP Multi Criteria Optimisation and Preference Modelling 289

6.1 Integrating LP Multi Criteria optimisation with Preference Modelling using fixed weight factors 290

6.2 Accounting for decision variable dependent preferences 291

6.3 Conclusions 292

7 Non-linear optimisation 293

7.1 Non-linear optimisation for exponential preference behaviour 293

7.2 Numerical example of an airport island in the North Sea 294

7.3 Conclusions 297

8 Geometric modelling 299

8.1 Allocation of activities to spaces 299

8.2 Fit of activities into spaces 302

8.3 Old city preservation example 303

8.4 Reflection in action: the urban decision room 306

8.5 Conclusions 307

II Cases 309

9 Linear Programming with negotiable constraints 311

9.1 Parties concerned, their targets and means 312

9.2 Model usage 312

9.3 Conclusions 319

10 Monte Carlo simulation 321

10.1 Multiple regression analysis including the effect of a lift 321

10.2 Monte Carlo simulation 321

11 Network planning & risk assessment 325

11.1 Project network of activities 325

11.2 Path ranking on slack (deterministic) 325

11.3 Path ranking on risk (probabilistic) 326

11.4 Conclusions 326

12 Regression analysis: residential real estate 329

12.1 Determine object properties that might be relevant 329

12.2 Analyse database using correlation analysis 331

12.3 Single variable regression analysis 333

12.4 Multiple regression analysis 334

12.5 Conclusions 335

13 Preference Measurement: The key to incorporating soft variables 337

13.1 The case of military airport Valkenburg 337

14 Integrating LP Multi Criteria Optimisation and Preference Modelling 345

15 Multi Criteria Optimisation 351

15.1 Rational and irrational decision making 351

15.2 Airport in the North Sea, a rational but probably infeasible option for Schiphol, Amsterdam 352

15.3 A European airport in the North Sea, a rational and feasible option for the European main airports 356

15.4 Conclusions 358

16 Non-linear, local, optimisation 359

16.1 Optimisation of ROI 359

16.2 Optimisation of shuttle speed 361

16.3 Conclusions 362

17 Geometric modelling 363

17.1 The first numerical model 363

17.2 The second numerical model linked to a geometrical model 365

17.3 Conclusions 366

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