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Modelling Empty Container Repositioning Logistics by Dong-Ping Song (English) Ha
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- ISBN-13
- 9783030933821
- Type
- NA
- Publication Name
- NA
- ISBN
- 9783030933821
- Book Title
- Modelling Empty Container Repositioning Logistics
- Publisher
- Springer International Publishing A&G
- Item Length
- 9.3 in
- Publication Year
- 2022
- Format
- Hardcover
- Language
- English
- Illustrator
- Yes
- Genre
- Technology & Engineering, Business & Economics
- Topic
- Industrial Engineering, Industrial Management, Manufacturing, Production & Operations Management
- Item Weight
- 15.4 Oz
- Item Width
- 6.1 in
- Number of Pages
- IX, 166 Pages
關於產品
Product Identifiers
Publisher
Springer International Publishing A&G
ISBN-10
3030933822
ISBN-13
9783030933821
eBay Product ID (ePID)
26057290288
Product Key Features
Book Title
Modelling Empty Container Repositioning Logistics
Number of Pages
IX, 166 Pages
Language
English
Topic
Industrial Engineering, Industrial Management, Manufacturing, Production & Operations Management
Publication Year
2022
Illustrator
Yes
Genre
Technology & Engineering, Business & Economics
Format
Hardcover
Dimensions
Item Weight
15.4 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Dewey Edition
23
Number of Volumes
1 vol.
Dewey Decimal
658.787
Table Of Content
Part I.- Chapter 1. Container logistics chain and empty container repositioning (ECR).- Part II .- Chapter 2. Closed-form optimal ECR policy in a single depot with random demand.- Chapter 3. Optimal ECR policy in two-depot stochastic systems: periodic-review.- Chapter 4. Optimal ECR policy in two-depot stochastic systems: continuous-review.- Chapter 5. Optimal and near-optimal ECR policies in hub-and-spoke stochastic systems.- Chapter 6. Container sharing and ECR in two-depot stochastic systems.- Chapter 7. Optimal ECR in general inland transport systems with uncertainty.- Part III.- Chapter 8. Container fleet sizing and ECR in shipping route with uncertain demands.- Chapter 9. Container fleet sizing and ECR in shipping service considering inland transport times with uncertainty.- Chapter 10. Container lease term optimisation and ECR in shipping route with uncertain demand.- Chapter 11. Evaluate flexible destination port ECR policy in shipping route with uncertain demand.- Chapter12. Laden container routing and ECR in shipping network with multiple service routes.- Chapter 13. Discrete-event driven simulation model for laden container distribution and ECR in shipping network.- Chapter 14. Evaluate ECR policies in liner shipping systems using simulation model.- Chapter 15. Conclusions.
Synopsis
The book takes the inventory control perspective to tackle empty container repositioning logistics problems in regional transportation systems by explicitly considering the features such as demand imbalance over space, dynamic operations over time, uncertainty in demand and transport, and container leasing phenomenon. The book has the following unique features. First, it provides a discussion of broad empty equipment logistics including empty freight vehicle redistribution, empty passenger vehicle redistribution, empty bike repositioning, empty container chassis repositioning, and empty container repositioning (ECR) problems. The similarity and unique characteristics of ECR compared to other empty equipment repositioning problems are explained. Second, we adopt the stochastic dynamic programming approach to tackle the ECR problems, which offers an algorithmic strategy to characterize the optimal policy and captures the sequential decision-making phenomenon in anticipation of uncertainties over time and space. Third, we are able to establish closed-form solutions and structural properties of the optimal ECR policies in relatively simple transportation systems. Such properties can then be utilized to construct threshold-type ECR policies for more complicated transportation systems. In fact, the threshold-type ECR policies resemble the well-known (s, S) and (s, Q) policies in inventory control theory. These policies have the advantages of being decentralized, easy to understand, easy to operate, quick response to random events, and minimal on-line computation and communication. Fourth, several sophisticated optimization techniques such as approximate dynamic programming, simulation-based meta-heuristics, stochastic approximation, perturbation analysis, and ordinal optimization methods are introduced to solve the complex stochastic optimization problems. The book will be of interest to researchers and professionals in logistics, transport, supply chain,and operations research., Part I (Chaps. 1), Chapter 1. Container logistics chain and empty container repositioning (ECR)Maritime logistics and container logisticsContainer logistics chainImportance of empty container repositioningReasons for empty container repositioningModelling methods for empty container repositioningReferences In Part II (Chaps. 2 7), Chapter 2. Closed-form optimal ECR policy in a single depot with random demand IntroductionA fluid flow model based on continuous-time dynamic programmingStructural properties of the optimal policy Solving the Hamilton-Jacobi-Bellman equationsExtension to more general casesNumerical examples Summary and notesReferences Chapter 3. Optimal ECR policy in two-depot stochastic systems: periodic-reviewIntroductionA discrete stochastic dynamic programming modelOptimal ECR policy and its structural propertiesNear-optimal threshold policyNumerical examplesSummary and notesReferences Chapter 4. Optimal ECR policy in two-depot stochastic systems: continuous-reviewIntroductionDiscounted cost caseConvert into discrete-time Markov decision processOptimal ECR policy and its structural propertiesClosed-form objective function and optimal threshold valuesNumerical examplesLong-run average cost caseConvert into discrete-time Markov decision processStationary distribution under threshold control policyOptimality of threshold control policyNumerical examplesSummary and notesReferences Chapter 5. Optimal and near-optimal ECR policies in hub-and-spoke stochastic systemsIntroduction Convert into discrete-time Markov decision processOptimal ECR policySuboptimal policy using a dynamic decomposition procedureNumerical examplesSummary and notesReferences Chapter 6. Container sharing and ECR in two-depot stochastic systemsIntroductionOptimal ECR policy without container sharingOptimal ECR policy with container sharingPractical ECR policies Numerical examplesSummary and notesReferences Chapter 7. Optimal ECR in general inland transport systems with uncertaintyIntroductionChance-constrained programming modelRobust optimisation modelInventory control modelSummary and notesReferences Part III. (Chaps. 8 15), Chapter 8. Container fleet sizing and ECR in shipping route with uncertain demandsIntroductionProblem formulationSolution methodsParameterized rule-based policyHeuristic policySimulation-based evolutionary optimisationCase studiesSummary and notesReferences Chapter 9. Container fleet sizing and ECR in shipping service considering inland transport times with uncertaintyIntroductionProblem formulationA rule-based operational policySimulation-based optimisationCase studiesSummary and notesReferences Chapter 10. Container lease term optimisation and ECR in shipping route with uncertain demandIntroductionProblem descriptionContainer lease term optimisation modelOperational rules in dynamic shipping systemsSolution procedure to optimise lease termsCase studiesSummary and notesReferences
LC Classification Number
HD38.5
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