Integrating packing and distribution problems and optimization through mathematical programming

Miguel, Fábio; Frutos, Mariano; Tohmé, Fernando; Méndez, Máximo

doi:10.5267/j.dsl.2015.10.002

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…The CVRP-TW, in turn, can adopt different variants, since time windows may exit for different elements of the service, be it the time of arrival at the clients' stores, the working time of drivers, the hours of activity of depots, etc. [26]- [33]. Finally, the Time Dependent Vehicle Routing Problem (TD-CVRP), takes into account the variations of traffic density in different areas, causing fluctuations in the speed of the vehicles, independently of the distances traveled.…”

Section: Literature Reviewmentioning

confidence: 99%

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A Decision Support Tool for Urban Freight Transport Planning Based on a Multi-Objective Evolutionary Algorithm

et al. 2019

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We present an optimization procedure based on a hybrid version of an evolutionary multiobjective decision-making algorithm for its application in urban freight transportation planning problems. This tool is intended to solve the planning problems of a merchandise distribution firm that dispatches small volume fractional loads of fresh foods on daily schedules. The firm owns a network of distribution centers supplying a large number of small businesses in Buenos Aires and its surroundings. The recombination operator of the evolutionary algorithm used here has been designed specifically for this problem. It is intended to embody a strategy that takes into account constraints like temporary closeness, closeness time window and connectivity in order to improve its performance in the clustering phase. The representation allows incorporating specific information about the actual instances of the problem and uses adaptive control of the parameters in the calibration stage. The performance of the proposed optimizer was tested against the results obtained by two evolutionary algorithms, NSGA II and SPEA 2, widely used in similar problems. We use hypervolume as a measure of convergence and dispersion of Pareto fronts. The statistical analysis of the results obtained with the three algorithms uses the Wilcoxon rank sum test, which yields evidence that our procedure provides good results.

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Section: Literature Reviewmentioning

confidence: 99%

“…Exact techniques (in small instances) have been used in [16], [20], [27], [28]. Among the heuristical methods used we can find local search [39], two-phase heuristics [22] and insertion heuristics [32], and combination heuristics [26].…”

Section: Literature Reviewmentioning

confidence: 99%

A Decision Support Tool for Urban Freight Transport Planning Based on a Multi-Objective Evolutionary Algorithm

et al. 2019

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The evolution of rectangular bin packing problem — A review of research topics, applications, and cited papers

Mezghani¹,

Haddar²,

Chabchoub³

2023

JIMO

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Bin packing problem (BPP) is one of the fastest-growing research issues within the field of combinatorial optimization. Over the last years, several studies carried out various BPP variants, mathematical models, and proposed methods to the BPPs. The classical BPP consists of packing a set of rectangular items in a minimum number of rectangular bins while respecting some constraints.Throughout the years, an improved typology was introduced by Wäscher et al. (2007), providing an excellent instrument for the organization and categorization criteria that defined the problem categories different from those of Dyckhoff (1990). Several early literature reviews have been conducted on various aspects of related packing problem variants.The contribution of this paper is to provide a comprehensive and refined taxonomy intended for BPPs. In addition to that, it is an up-to-date review based on a chronological taxonomy of the literature and depicts further research horizons.This systematic review allowed us to identify other characteristics and constraints, based on Wäscher's original ideas, mainly distinguished according to real cases studies. The detailed analysis provides a valuable framework for understanding the research gaps for future studies that should be acknowledged while proposing and solving new extensions.

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Integrating packing and distribution problems and optimization through mathematical programming

Miguel¹,

Frutos²,

Tohmé³

et al. 2016

10.5267/j.dsl

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This paper analyzes the integration of two combinatorial problems that frequently arise in production and distribution systems. One is the Bin Packing Problem (BPP) problem, which involves finding an ordering of some objects of different volumes to be packed into the minimal number of containers of the same or different size. An optimal solution to this NP-Hard problem can be approximated by means of meta-heuristic methods. On the other hand, we consider the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW), which is a variant of the Travelling Salesman Problem (again a NP-Hard problem) with extra constraints. Here we model those two problems in a single framework and use an evolutionary meta-heuristics to solve them jointly. Furthermore, we use data from a real world company as a test-bed for the method introduced here.

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Integrating packing and distribution problems and optimization through mathematical programming

Cited by 3 publications

References 14 publications

A Decision Support Tool for Urban Freight Transport Planning Based on a Multi-Objective Evolutionary Algorithm

A Decision Support Tool for Urban Freight Transport Planning Based on a Multi-Objective Evolutionary Algorithm

The evolution of rectangular bin packing problem — A review of research topics, applications, and cited papers

Integrating packing and distribution problems and optimization through mathematical programming

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