The impact of loading restrictions on the two-echelon location routing problem

Gandra, Vinícius; Çalık, Hatice; Wauters, Tony; Toffolo, Túlio A. M.; Carvalho, Marco Antonio Moreira de; Berghe, Greet Vanden

doi:10.1016/j.cie.2021.107609

Cited by 8 publications

(4 citation statements)

References 43 publications

(54 reference statements)

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“…In a separate study, Gandra et al, [10] introduced a generalized 2E-LRP model that incorporates two-dimensional loading constraints for the 2E-LRP. They addressed this model with a heuristic optimization method that accounts for various loading scenarios and assesses its efficiency with reallife examples.…”

Section: Literature Reviewmentioning

confidence: 99%

Designing a Fuzzy Mathematical Model for a Two-Echelon Allocation-Routing Problem by Applying Route Conditions: A New Interactive Fuzzy Approach

Yadegari,

Molana,

Kashan

et al. 2024

Decis. Mak. Appl. Manag. Eng.

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In vehicle routing problems (VRP), the optimal allocation of transportation by considering factors such as route hardness, driver experience and vehicle worn-out has a significant effect on costs reduction and approaching real-world conditions. In this paper, a novel fuzzy mixed integer non-linear mathematical model to address the two-echelon allocation-routing problem under uncertainty is proposed by applying route and fleet conditions. The cost of allocating drivers to diverse vehicles is computed at the first echelon of the problem, considering factors such as vehicle type, vehicle wear-out, and driver experience. Additionally, different routes are defused with varying levels of hardness. The goal of the second echelon of the model is to improve reliability by defining the reliability of routes within each section. To solve the model, the Torabi and Hessini (TH), the Selimi and Ozkarahan (SO) methods, and a newly proposed approach (PIA) were utilized to transform the multi-objective model into a single-objective one. Numerical tests and performance indicators were used to validate the effectiveness of both the multi-objective mathematical model and the proposed solution method. The validation computation results indicate that the proposed solution approach outperforms both the TH and SO approaches.

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Section: Literature Reviewmentioning

confidence: 99%

Designing a Fuzzy Mathematical Model for a Two-Echelon Allocation-Routing Problem by Applying Route Conditions: A New Interactive Fuzzy Approach

Yadegari,

Molana,

Kashan

et al. 2024

Decis. Mak. Appl. Manag. Eng.

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“…Wang et al [ 42 ] modelled 2E-LRP considering multiple periods and shared transportation resource to find optimal facility locations as well as optimal routes in different periods during the decision horizon. Gandra et al [ 43 ] investigated the impact of loading restrictions on the two-echelon location-routing problem. Fallahtafti et al [ 44 ] presented a multi-objective two-echelon location-routing problem for cash logistics to reduce the risk of theft while transporting cash and solved the problem using meta-heuristic approaches.…”

Section: Literature Reviewmentioning

confidence: 99%

A two-echelon location routing problem considering sustainability and hybrid open and closed routes under uncertainty

Hajghani¹,

Forghani²,

Heidari³

et al. 2023

Heliyon

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“…As expected, "minimization of costs" was the objective function mostly used. In 37.5% (n=15) papers [8,37,20,43,4,14,52,38,39,6,49,7,19,28,13] it was aimed to minimize costs. Thanks to the increasing importance of green issues and sustainability, minimizing energy consumption [17] started to find place in the objective functions.…”

Section: 31mentioning

confidence: 99%

A bibliometric and social network analysis of data-driven heuristic methods for logistics problems

Deniz

Özceylan

2023

JIMO

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<p style='text-indent:20px;'>Transport and logistics systems include a range of activities that deal with all sorts of decisions and operations from material handling to vehicle routing. One of the main challenges for transport and logistics processes is to deal with large-scale and complex problems. However, with increasingly diverse sets of operational real-world data becoming available, data-driven heuristic approaches are promising to pave the path for solving the problems in the field of transport and logistics. Thus, a comprehensive review is needed to observe the reflections of this path in literature. To bridge this gap, a total of 40 papers on the topic of "data-driven heuristic approaches to logistics and transportation problems" are determined. Before the categorization and content analysis; descriptive, bibliometric and social network analysis are carried out to identify the current state of the literature. All the papers are systemically reviewed based on different perspectives, namely data-driven methodology, heuristics, sub-problems and etc. Based on the review, suggestions for future research are likewise provided. Subsequently, machine learning and deep learning methods are considered to be among the most promising data-driven methodologies. The review may be useful for academicians, researchers, and practitioners for a better understanding of data-driven heuristic approaches to transportation and logistics problems.</p>

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The impact of loading restrictions on the two-echelon location routing problem

Cited by 8 publications

References 43 publications

Designing a Fuzzy Mathematical Model for a Two-Echelon Allocation-Routing Problem by Applying Route Conditions: A New Interactive Fuzzy Approach

Designing a Fuzzy Mathematical Model for a Two-Echelon Allocation-Routing Problem by Applying Route Conditions: A New Interactive Fuzzy Approach

A two-echelon location routing problem considering sustainability and hybrid open and closed routes under uncertainty

A bibliometric and social network analysis of data-driven heuristic methods for logistics problems

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