Combining Mobile Robotics and Packing for Optimal deliveries

Rhiat, Ahmed; Aggoun, Abderrahmane; Lachere, R.

doi:10.1016/j.promfg.2020.02.258

Cited by 4 publications

(1 citation statement)

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“…In this study, we propose an adaptation of the Positions and Covering (P&C) methodology, used by [ 10 ] to obtain optimal solutions for the two-dimensional bin packing problem. Considering the similarity of the 2SP with other packing problems, some potential applications for the P&C methodology can be found in agricultural fields to delineate rectangular and homogeneous management zones [ 11 – 13 ], in scheduling problems applied to environmental, automotive, ferry, and manufacturing industries to ensure maximum use of materials [ 14 – 16 ], in healthcare applied to operating rooms schedules [ 17 – 19 ], in cloud computing where a set of jobs must be processed on virtual machines of physical servers with the aim of improves the energy efficiency [ 20 – 22 ], and in optimal deliveries in e-commerce where the objective is optimizing the total number of containers to integrate into several delivery trips [ 23 ].…”

Section: Introductionmentioning

confidence: 99%

Exact solutions for the 2d-strip packing problem using the positions-and-covering methodology

Cid-García

Ríos-Solís

2021

PLoS ONE

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We use the Positions and Covering methodology to obtain exact solutions for the two-dimensional, non-guillotine restricted, strip packing problem. In this classical NP-hard problem, a given set of rectangular items has to be packed into a strip of fixed weight and infinite height. The objective consists in determining the minimum height of the strip. The Positions and Covering methodology is based on a two-stage procedure. First, it is generated, in a pseudo-polynomial way, a set of valid positions in which an item can be packed into the strip. Then, by using a set-covering formulation, the best configuration of items into the strip is selected. Based on the literature benchmark, experimental results validate the quality of the solutions and method’s effectiveness for small and medium-size instances. To the best of our knowledge, this is the first approach that generates optimal solutions for some literature instances for which the optimal solution was unknown before this study.

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Section: Introductionmentioning

confidence: 99%

Exact solutions for the 2d-strip packing problem using the positions-and-covering methodology

Cid-García

Ríos-Solís

2021

PLoS ONE

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A Multi-object Detection for Classification System Using Machine Learning and Robotic Manipulator

Jonathan,

Paul,

Jorge

et al. 2024

Lecture Notes in Networks and Systems

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Metaheuristic algorithms for one-dimensional bin-packing problems: A survey of recent advances and applications

Munien

Ezugwu

2021

Journal of Intelligent Systems

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The bin-packing problem (BPP) is an age-old NP-hard combinatorial optimization problem, which is defined as the placement of a set of different-sized items into identical bins such that the number of containers used is optimally minimized. Besides, different variations of the problem do exist in practice depending on the bins dimension, placement constraints, and priority. More so, there are several important real-world applications of the BPP, especially in cutting industries, transportation, warehousing, and supply chain management. Due to the practical relevance of this problem, researchers are consistently investigating new and improved techniques to solve the problem optimally. Nature-inspired metaheuristics are powerful algorithms that have proven their incredible capability of solving challenging and complex optimization problems, including several variants of BPPs. However, no comprehensive literature review exists on the applications of the metaheuristic approaches to solve the BPPs. Therefore, to fill this gap, this article presents a survey of the recent advances achieved for the one-dimensional BPP, with specific emphasis on population-based metaheuristic algorithms. We believe that this article can serve as a reference guide for researchers to explore and develop more robust state-of-the-art metaheuristics algorithms for solving the emerging variants of the bin-parking problems.

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Combining Mobile Robotics and Packing for Optimal deliveries

Cited by 4 publications

References 1 publication

Exact solutions for the 2d-strip packing problem using the positions-and-covering methodology

Exact solutions for the 2d-strip packing problem using the positions-and-covering methodology

A Multi-object Detection for Classification System Using Machine Learning and Robotic Manipulator

Metaheuristic algorithms for one-dimensional bin-packing problems: A survey of recent advances and applications

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