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Springer Logistics, Supply Chain & Financial Predictive Analytics

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Description

This comprehensive guide from Springer addresses critical challenges in financial analysis, logistics and supply chain management through advanced predictive analytics and big data approaches. Spanning twenty chapters, the book explores contemporary topics including co-operative and non-cooperative supply chain models for imperfect quality items with trade-credit financing, non-dominated sorting water cycle algorithms for portfolio optimisation, and methods for determining initial, basic and feasible solutions in transportation problems. Designed for professionals seeking to integrate analytics into decision-making across banking, logistics and supply chain operations, this resource combines theoretical foundations with practical applications to enhance organisational efficiency and financial performance.

Key Features

Covers big data analytics applications in the banking sector and financial analysis within modern supply chain contexts.

Explores co-operative and non-cooperative supply chain models designed specifically for imperfect quality items with trade-credit financing arrangements.

Presents advanced algorithmic solutions including non-dominated sorting water cycle algorithm for cardinality constrained portfolio problems.

Provides practical methods for determining initial, basic and feasible solutions applicable to transportation and logistics challenges.

Comprises twenty chapters addressing real-world problems commonly encountered in logistics, supply chain management and financial decision-making.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
29 December 2018
Listed Since
28 December 2018

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