Ant Colony Optimization solutions for logistic route planning with pick-up and delivery

Lu, Erl-Huei; Yang, Ying-Chen; Su, Zeal Li-Tse

doi:10.1109/smc.2016.7844340

Cited by 4 publications

(2 citation statements)

References 8 publications

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“…19 Recalling that the implementation is based on the orientation discrimination it is necessary to know the Cartesian points and the orientation elements by means of a homogeneous transformation matrix that defines the trajectory sequence. As shown in equations (13) and (15), these functions represent the path that the manipulator follows in x and y coordinates of a sinusoidal and a spiral function, where equations (14) and (16) represent their final position and orientation of the end-effector.…”

Section: Forward Kinematics and Manipulator Elbow-configurationmentioning

confidence: 99%

“…They are approximated techniques for solving hard problems established as optimization cases. These algorithms are used in different engineering areas such as mechanism synthesis, 12 the design of electromagnetic devices, 13 delivery planning, 14 network routing, 15 among others. In this work, a novel methodology for avoiding robotic singularities in a trajectory is proposed, by establishing an optimization problem with a weighted objective function that modifies the position and/or orientation in the Euclidean space, enabling the manipulator to maintain its reference direction concerning to the original target.…”

Section: Introductionmentioning

confidence: 99%

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Metaheuristic techniques comparison to optimize robotic end-effector behavior and its workspace

Funes-Lora

Portilla-Flores

Rivera-Blas

et al. 2018

International Journal of Advanced Robotic Systems

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Many robots are dedicated to replicate trajectories recorded manually; the recorded trajectories may contain singularities, which occur when positions and/or orientations are not achievable by the robot. The optimization of those trajectories is a complex issue and classical optimization methods present a deficient performance when solving them. Metaheuristics are well-known methodologies for solving hard engineering problems. In this case, they are applied to obtain alternative trajectories that pass as closely as possible to the original one, reorienting the end-effector and displacing its position to avoid the singularities caused by limitations of inverse kinematics equations, the task, and the workspace. In this article, alternative solutions for an ill-posed problem concerning the behavior of the robotic endeffector position and orientation are proposed using metaheuristic algorithms such as cuckoo search, differential evolution, and modified artificial bee colony. The case study for this work considers a three-revolute robot (3R), whose trajectories can contain or not singularities, and an optimization problem is defined to minimize the objective function that represents the error of the alternative trajectories. A tournament in combination with a constant of proportionality allows the metaheuristics to modify the gradual orientation and position of the robot when a singularity is present. Consequently, the procedure selects from all the possible elbow-configurations the best that fits the trajectory. A classical numerical technique, Newton's method, is used to compare the results of the applied metaheuristics, to evaluate their quality. The results of this implementation indicate that metaheuristic algorithms are an efficient tool to solve the problem of optimizing the end-effector behavior, because of the quality of the alternative trajectory produced.

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Section: Forward Kinematics and Manipulator Elbow-configurationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Metaheuristic techniques comparison to optimize robotic end-effector behavior and its workspace

Funes-Lora

Portilla-Flores

Rivera-Blas

et al. 2018

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

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Multi-task Assignment of Logistics Distribution based on Modified Ant Colony Optimization

Lin

Cheng

et al. 2018

2018 Chinese Automation Congress (CAC)

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Path Optimization and Logistics Economic Benefits Based on Sparsely Sampled GPS Trajectory Data

Lan

2022

Mobile Information Systems

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Affected by the technological revolution of the Internet and the rise of e-commerce, the logistics, and transportation industry has become the main artery of the economy, and higher requirements are placed on logistics and distribution. Nowadays, how to minimize the cost of logistics distribution is an important research goal of logistics economic benefits. To this end, this article investigates and discusses the logical distribution based on interval variables, and on the basis of previous studies, has carried out some fruitful research and attempts on the logical distribution model and solving algorithm. The beginning of this article explains the research background and the importance of this article. Analyzed and reviewed the current research status at home and abroad, and pointed out that the fuzzy and probabilistic methods used in previous studies to describe the variable assumptions used were too strong. The method used in this article to characterize interval variables does not need to know the probability distribution and density function that the variables obey, so it has more applicability. However, in view of the widespread popularity of sensor equipment and mobile communication equipment, more and more sparsely sampled trajectories, such as road patrol data, company employee check-in data, and base station data, are always poorly sampled for flight path data used to connect to mobile phones. The method of collecting this type of data is different from traditional GPS data and does not require items with GPS positioning equipment. The scanning width is much better than traditional trajectory data, but the scanning accuracy of a single object is insufficient. The intersection recognition method based on GPS trajectory data effectively improves the economic benefits of logistics transportation. In this paper, the study of sparsely sampled GPS trajectory data and intersection identification methods is applied to improve the economic efficiency of logistics and promote the development of the economic efficiency of logistics.

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Ant Colony Optimization solutions for logistic route planning with pick-up and delivery

Cited by 4 publications

References 8 publications

Metaheuristic techniques comparison to optimize robotic end-effector behavior and its workspace

Metaheuristic techniques comparison to optimize robotic end-effector behavior and its workspace

Multi-task Assignment of Logistics Distribution based on Modified Ant Colony Optimization

Path Optimization and Logistics Economic Benefits Based on Sparsely Sampled GPS Trajectory Data

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