Part commonality effects on integrated network design and inventory models for low-demand service parts logistics systems

Jeet, Vishv; Kutanoğlu, Erhan

doi:10.1016/j.ijpe.2018.09.017

Cited by 8 publications

(1 citation statement)

References 21 publications

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“…In addition, the relationship between the location of logistics facilities and vehicle travel distances for shipments associated with the facilities has also been analyzed [52]. Some other conventional approaches to location include heuristics [53], MIP models [54] dynamic programming [55], nonlinear programming [56,57], quadratic programming [58,59], hierarchical analysis process (AHP) [60], and artificial intelligence (AI) techniques [61], such as specialist systems, artificial neural networks (ANNs), metaheuristics or fuzzy set theory [62]. In the recent works, the trend is to consider a large part of the logistics distribution network incorporating the other vertices of the logistics triangle (transport and inventory), to propose increasingly compensatory solutions.…”

Section: Related Literaturementioning

confidence: 99%

Location of Urban Logistics Spaces (ULS) for Two-Echelon Distribution Systems

Ruiz-Meza

Meza-Peralta

Montoya‐Torres

et al. 2021

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The main concern in city logistics is the need to optimize the movement of goods in urban contexts, and to minimize the multiple costs inherent in logistics operations. Inspired by an application in a medium-sized city in Latin America, this paper develops a bi-objective mixed linear integer programming (MILP) model to locate different types of urban logistics spaces (ULS) for the configuration of a two-echelon urban distribution system. The objective functions seek to minimize the costs associated with distance traveled and relocation, in addition to the costs of violation of time windows. This model considers heterogeneous transport, speed assignment, and time windows. For experimental evaluation, two operational scenarios are considered, and Pareto frontiers are obtained to identify the efficient non-dominated solutions to select the most feasible ones from such a set. A case study of a distribution company of goods for supermarkets in the city of Barranquilla, Colombia, is also used to validate the proposed model. These solutions allow decision-makers to define the configuration of ULS networks for urban product delivery.

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