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Article
Publication date: 1 February 1991

Dynamic Vehicle Scheduling: An Expert Systems Approach

Prabir K. Bagchi and Barin N. Nag

The dynamic vehicle scheduling problem for a shipper involvesmanaging transport of freight originating at various locations tominimise transport costs. The job involves…

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Abstract

The dynamic vehicle scheduling problem for a shipper involves managing transport of freight originating at various locations to minimise transport costs. The job involves dynamic assignment of vehicles contracted from carriers to loads available at multiple locations on a real time basis. A framework for building a PC‐based expert system to be used as a decision support system is provided. An example expert scheduling system (EXLOAD) built on VP EXPERT, a PC‐based expert system shell is also shown.

Details

International Journal of Physical Distribution & Logistics Management, vol. 21 no. 2
Type: Research Article
DOI: https://doi.org/10.1108/09600039110134805
ISSN: 0960-0035

Keywords

  • Decision‐support systems
  • Physical distribution management
  • Vehicle scheduling
  • Freight transport

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Article
Publication date: 1 April 2014

Mapping supply chain strategy: an industry analysis

Barin Nag, Chaodong Han and Dong-qing Yao

In manufacturing industries, the levels of inventories at all stages (i.e. raw material, work-in-process and finished goods inventories) indicate the firm's competitive…

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Abstract

Purpose

In manufacturing industries, the levels of inventories at all stages (i.e. raw material, work-in-process and finished goods inventories) indicate the firm's competitive positioning, strategies, internal processes and relationships with suppliers and downstream customers. The authors identify patterns of manufacturing industries based on levels of raw material and finished goods inventories to classify inbound and outbound supply chain strategies.

Design/methodology/approach

The authors review literature on supply chain inventory strategy and perform cluster analysis to analyze patterns of manufacturing industries based on manufacturing industry data collected from US Census of Bureau. Following Porter's Five Forces Model, the authors perform in-depth case studies of four representative industries to analyze factors driving supply chain strategies, including industry intensity of rivalry, threat of new entrants, threat of substitutes, bargaining power of suppliers, and bargaining power of buyers.

Findings

This study identifies three streams of research on supply chain strategy: Fisher's model and its variations, lean and agile paradigms, and push/pull systems. It finds that whether an industry shows low or high raw materials or finished goods inventories depending on its products, processes, and the dynamics of all forces described in the Five Forces Model.

Research limitations/implications

This study is not able to include supplier selection, production strategies, warehousing and distribution, and even product design into the analysis of supply chain strategy due to data limitation. This study classifies industries based on average inventory levels of raw materials and finished goods, while inventory levels and supply chain strategies for specific firms may vary significantly within each industry.

Originality/value

This study contributes to the supply chain management literature by providing a parsimonious framework of mapping inbound and outbound supply chain inventory strategies, and the results based on the analyses of all US manufacturing industries provide a baseline picture for supply chain management professionals with manufacturing firms.

Details

Journal of Manufacturing Technology Management, vol. 25 no. 3
Type: Research Article
DOI: https://doi.org/10.1108/JMTM-06-2012-0062
ISSN: 1741-038X

Keywords

  • Competitive strategy
  • Supply chain management
  • Cluster analysis
  • Manufacturing industry
  • Inventory

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