运输规划中货运整合的创新建模框架

IF 1.7 Q3 MANAGEMENT

IIMB Management Review Pub Date : 2025-03-01 DOI:10.1016/j.iimb.2025.100550

Manoj Kumar , Anoop K. P.

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An innovative modelling framework for freight consolidation in transportation planning

This paper addresses freight consolidation in rail transportation planning. Multiple demand destinations are served in a single trip to utilise the volume discount on freight rate. An efficient mixed-integer linear programming (MILP) based modelling framework is proposed to optimally allocate rail wagons to a given set of destinations considering the shipment options offered by Indian Railways. Twelve problem instances are derived using real data from an Indian food grain organisation and are solved to optimum using the CPLEX solver in quick time. The results indicate that multi-point orders can reduce the total transportation cost and ease the handling of shipments at terminals.

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来源期刊

IIMB Management Review MANAGEMENT-

CiteScore

3.20

自引率

5.90%

发文量

审稿时长

68 days

期刊介绍： IIMB Management Review (IMR) is a quarterly journal brought out by the Indian Institute of Management Bangalore. Addressed to management practitioners, researchers and academics, IMR aims to engage rigorously with practices, concepts and ideas in the field of management, with an emphasis on providing managerial insights, in a reader friendly format. To this end IMR invites manuscripts that provide novel managerial insights in any of the core business functions. The manuscript should be rigorous, that is, the findings should be supported by either empirical data or a well-justified theoretical model, and well written. While these two requirements are necessary for acceptance, they do not guarantee acceptance. The sole criterion for publication is contribution to the extant management literature.Although all manuscripts are welcome, our special emphasis is on papers that focus on emerging economies throughout the world. Such papers may either improve our understanding of markets in such economies through novel analyses or build models by taking into account the special characteristics of such economies to provide guidance to managers.