Earliest finish time, 392, 393, 394

Earliest possible time, 402

Earliest start time, 392, 393, 400, 410

Econometric models, 485

Economic order quantity (EOQ), 189–194, 200, 471

• assumptions of, 189, 191

• formula, 191–192

• without instantaneous receipt assumption, 196–199

Economic systems and simulation, 462, 463, 485

Efficiency of sample information, 82

Elimination method, 248

Empirical rule and normal distribution, 44, 45

Employee scheduling applications, 299–300

EMV. See Expected monetary value (EMV)

Enterprise resource planning (ERP), 220–221

Enumeration and integer programming problems, 358

EOL. See Expected opportunity loss (EOL)

Equally likely, 67, 68

Equilibrium conditions, 507–510, 514

Equilibrium probabilities, 505, 507

Equilibrium share, 507

Equilibrium states, 507, 509, 510

Erlang, A. K., 428

Errors, 113

• with constant variance, 117

• forecast, 151

• independent, 117

• with a mean of zero, 117

• normally distributed, 117

Error variance, 119

Events, 25–27

• and activities, 387

• collectively exhaustive, 23–24, 32

• constraints, 408

• dependent and independent, 26–27

• mutually exclusive, 23–24, 32

• statistically independent, 26

• union of, 25

Excel, 9–12

• add-ins, 11, 485

• for analysis of Arnold’s multichannel queuing model, 441

• on Arnold’s Muffler shop queue, 436

• assignment problems, 327

• binomial probabilities, 38

• box filling example, 535–536

• for the Brown Manufacturing Problem, 198–199

• c-chart, 540–541

• constant service time model, 443

• Data Analysis add-in, 11, 122

• decision theory problems, 75–77, 85

• decomposition method, 170

• developing regression model, 122–124, 133–134

• to develop multiple regression model, 127, 128

• to develop regression model, 170, 171

• dummy variables and, 129, 130

• economic order quantity (EOQ), 193

• Excel 2016, 9, 11, 44, 46

• Excel POM-QM, 9–12

• Excel spreadsheets, 9–12, 34

• F distribution, 46

• finding exponential probabilities, 48

• finite population model, 445

• forecasting, 158–160

• Goal Seek, 11, 12

• integer programming model, 361, 363

• integer programming problems, 360

• integer solutions, 305

• labor planning solution, 301

• linear programming (LP) problems, 251, 252–257

• linear regression equation, 132–134

• Markov analysis with, 526–528

• maximal-flow problems, 331–332

• mean, variance, and standard deviation, 34

• minimal spanning tree problem, 336–337

• minimization problems, 260–261

• nonlinear relationship, 132

• and payoff table problems, 75–77

• p-chart, 539

• and Poisson distribution, 49, 50

• for Port of New Orleans simulation, 478

• probability distribution of a continuous random variable, 34

• production run models, 198–199

• program crashing, 409

• program evaluation and review technique/ critical path method (PERT/CPM), 398–399

• quantity discount problems, 202–203

• random numbers, generating, 471

• regression calculations, 122, 123–124

• regression line, 163–164

• safety stock and reorder point, 208–209

• shortest-route problems, 333–334

• simulation, 469–471

• simulation module, 471

• Solver add-in, 11, 252–255

• Solver and changes in right-hand-side values, 270–271

• Solver and objective function coefficients change, 267–268

• for the Sumco Pump Company example, 193

• sum of squares error, 122

• Sumproduct function, 253

• for Super Cola example, 536

• and transportation problems, 321–322, 324–325

• transshipment problems, 330

• trend-adjusted exponential smoothing, 162

• trend analysis, 163–164

• used for normal probability distribution, 44

• Whole Food Diet solution, 206

Excel QM

• box filling example, 535–536

• c-charts and, 540–541

• linear programming problems, 255–257

• p-chart and, 539, 547

Executive Furniture Corporation, 320, 322

Expected activity time, 392, 394

Expected demand, 467

Expected monetary value (EMV), 69–70, 77, 78, 79, 80, 81

Expected opportunity loss (EOL), 71–72

Expected utility, 89

Expected value for activity completion times, 391

Expected value of perfect information (EVPI), 70–71, 75

Expected value of probability distribution, 32–33

Expected value of sample information (EVSI), 81–82

Expected value with perfect information (EVwPI), 70–71

Expenses, 6

Explanatory variable, 111

Exponential distribution, 35, 46–48, 49, 465

Exponential service times, 434–441

Exponential smoothing, 153, 156–158

• and Midwestern Manufacturing, 161, 162

• with trend model, 160–163

ExtendSim, 485

Extreme point, 248. See also Corner point method