LEADER 05795nam 2200733 a 450 001 9910143426903321 005 20200520144314.0 010 $a1-280-95701-8 010 $a9786610957019 010 $a0-470-17005-0 010 $a0-470-17004-2 035 $a(CKB)1000000000354897 035 $a(EBL)309787 035 $a(OCoLC)476092178 035 $a(SSID)ssj0000182516 035 $a(PQKBManifestationID)11156506 035 $a(PQKBTitleCode)TC0000182516 035 $a(PQKBWorkID)10171995 035 $a(PQKB)11096951 035 $a(MiAaPQ)EBC309787 035 $a(EXLCZ)991000000000354897 100 $a20070209d2007 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aIntroduction to distribution logistics /$fPaolo Brandimarte, Giulio Zotteri 210 $aHoboken, N.J. $cWiley-Interscience$dc2007 215 $a1 online resource (608 p.) 225 1 $aStatistics in practice 300 $aDescription based upon print version of record. 311 $a0-471-75044-1 320 $aIncludes bibliographical references and index. 327 $aIntroduction to Distribution Logistics; Contents; Preface; 1 Supply Chain Management; 1.1 What do we mean by logistics?; 1.1.1 Plan of the chapter; 1.2 Structure of production/distribution networks; 1.3 Competition factors, cost drivers, and strategy; 1.3.1 Competition factors; 1.3.2 Cost drivers; 1.3.3 Strategy; 1.4 The role of inventories; 1.4.1 A classical model: Economic order quantity; 1.4.2 Capacity-induced stock; 1.5 Dealing with uncertainty; 1.5.1 Setting safety stocks; 1.5.2 A two-stage decision process: Production planning in an assemble-to-order environment 327 $a1.5.3 Inventory deployment1.6 Physical flows and transportation; 1.7 Information flows and decision rights; 1.8 Time horizons and hierarchical levels; 1.9 Decision approaches; 1.10 Quantitative models and methods; 1.11 For further reading; References; 2 Network Design and Transportation; 2.1 The role of intermediate nodes in a distribution network; 2.1.1 The risk pooling effect: reducing the uncertainty level; 2.1.2 The role of distribution centers and transit points in transportation optimization; 2.2 Location and flow optimization models; 2.2.1 The transportation problem 327 $a2.2.2 The minimum cost flow problem2.2.3 The plant location problem; 2.2.4 Putting it all together; 2.3 Models involving nonlinear costs; W.2.4 Continuos-space location models; W.2.5 Retail-Store Location Models; 2.6 For further reading; References; 3 Forecasting; 3.1 Introduction; 3.2 The variable to be predicted; 3.2.1 The forecasting process; 3.3 Metrics for forecast errors; 3.3.1 The Mean Error; 3.3.2 Mean Absolute Deviation; 3.3.3 Root Mean Square Error; 3.3.4 Mean Percentage Error and Mean Absolute Percentage Error; 3.3.5 ME%, MAD%, RMSE%; 3.3.6 Theil's U statistic 327 $a3.3.7 Using metrics of forecasting accuracy3.4 A classification of forecasting methods; 3.5 Moving Average; 3.5.1 The demand model; 3.5.2 The algorithm; 3.5.3 Setting the parameter; 3.5.4 Drawbacks and limitations; 3.6 Simple exponential smoothing; 3.6.1 The demand model; 3.6.2 The algorithm; 3.6.3 Setting the parameter; 3.6.4 Initialization; 3.6.5 Drawbacks and limitations; 3.7 Exponential smoothing with trend; 3.7.1 The demand model; 3.7.2 The algorithm; 3.7.3 Setting the parameters; 3.7.4 Initialization; 3.7.5 Drawbacks and limitations; 3.8 Exponential smoothing with seasonality 327 $a3.8.1 The demand model3.8.2 The algorithm; 3.8.3 Setting the parameters; 3.8.4 Initialization; 3.8.5 Drawbacks and limitations; 3.9 Smoothing with seasonality and trend; 3.9.1 The demand model; 3.9.2 The algorithm; 3.9.3 Initialization; 3.10 Simple linear regression; 3.10.1 Setting up data for regression; W.3.11 Forecasting models based on multiple regression; 3.12 Forecasting demand for new products; 3.12.1 The Delphi method and the committee process; 3.12.2 Lancaster model: forecasting new products through product features; 3.12.3 The early sales model; 3.13 The bass model 327 $a3.13.1 Limitations and drawbacks 330 $aunique introduction to distribution logistics that focuses on both quantitative modeling and practical business issues Introduction to Distribution Logistics presents a complete and balanced treatment of distribution logistics by covering both applications and the required theoretical background, therefore extending its reach to practitioners and students in a range of disciplines such as management, engineering, mathematics, and statistics. The authors emphasize the variety and complexity of issues and sub-problems surrounding distribution logistics as well as the limitations and sco 410 0$aStatistics in practice. 606 $aNetwork analysis (Planning)$xMathematics 606 $aProduction scheduling$xStatistical methods 606 $aBusiness logistics$xStatistical methods 606 $aTraffic flow$xMathematical models 606 $aPhysical distribution of goods$xMathematics 606 $aDistribution (Probability theory) 615 0$aNetwork analysis (Planning)$xMathematics. 615 0$aProduction scheduling$xStatistical methods. 615 0$aBusiness logistics$xStatistical methods. 615 0$aTraffic flow$xMathematical models. 615 0$aPhysical distribution of goods$xMathematics. 615 0$aDistribution (Probability theory) 676 $a658.4/032 700 $aBrandimarte$b Paolo$0283971 701 $aZotteri$b Giulio$f1970-$0731160 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910143426903321 996 $aIntroduction to distribution logistics$91440337 997 $aUNINA