Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Heuristics

Heuristics

Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...

The Availability Heuristic

The Availability Heuristic

A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):

Statically Indeterminate Problem Solving

Statically Indeterminate Problem Solving

Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...

Design Example: Alignment of a Road Line Using GIS

Design Example: Alignment of a Road Line Using GIS

The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...

Distributed Loads: Problem Solving

Distributed Loads: Problem Solving

Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Prediction of inflammatory bowel disease recurrence risk based on multi-omics integration and machine learning models.

Computational biology and chemistry·2026

Same author

Scaled containment control for first/second-order multi-agent systems in a noisy environment.

ISA transactions·2026

Same author

Seal whisker-inspired fully printed MEMS flow sensor via micron-scale soft material additive manufacturing.

Microsystems & nanoengineering·2026

Same author

The Role of Different Thoughts in Tacit Coordination and Its Malleability by Interventions.

Journal of cognition·2026

Same author

Enhanced Multiagent Reinforcement-Learning-Aided Adaptive Fractional-Order EADRC for Load Frequency Control of Multiarea Power Systems.

IEEE transactions on cybernetics·2026

Same author

Propofol Attenuates Brain Ischemic Injury Through the Cannabinoid Type 1 (CB1) Receptor.

Cureus·2026

Same journal

A New Human-Likeness and Comfort Index for Robot Movements Along Prescribed Paths.

IEEE transactions on cybernetics·2026

Same journal

Robust Semiglobal and Global Stabilization for Nonlinear Normal Form Systems by Time-Varying Feedback.

IEEE transactions on cybernetics·2026

Same journal

Adaptive Global Asymptotic Output Stabilization of Uncertain Nonlinear Systems Under Dynamic State/Input Quantization.

IEEE transactions on cybernetics·2026

Same journal

Accelerated Distributed Gradient Tracking for Constrained Aggregative Optimization Over Time-Varying Digraphs.

IEEE transactions on cybernetics·2026

Same journal

Small-Gain-Based Plug-and-Play Distributed Control Framework for DC Microgrids With Decentralized Reconfiguration.

IEEE transactions on cybernetics·2026

Same journal

Prescribed-Time Impulsive Control of High-Order Integrator Systems.

IEEE transactions on cybernetics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Dec 26, 2025

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

Efficient Heuristic Algorithms for Single-Vehicle Task Planning With Precedence Constraints.

Xiaoshan Bai, Ming Cao, Weisheng Yan

IEEE Transactions on Cybernetics

|March 10, 2020

Summary

This summary is machine-generated.

This study addresses vehicle task planning with sequence constraints, developing new algorithms to minimize travel distance. The proposed methods offer efficient and effective solutions compared to genetic algorithms.

More Related Videos

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Published on: February 1, 2020

Related Experiment Videos

Last Updated: Dec 26, 2025

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Published on: February 1, 2020

Area of Science:

Operations Research
Computer Science
Artificial Intelligence

Background:

The vehicle routing problem with precedence constraints is complex.
Finding optimal solutions for task planning with sequence orders is computationally challenging.

Purpose of the Study:

To investigate the NP-hard task planning problem for a single vehicle visiting multiple targets with precedence constraints.
To minimize the total travel distance while adhering to all specified sequence orders.

Main Methods:

Constructing a lower bound for the optimal solution using graph theory.
Developing a novel topological sorting strategy inspired by existing techniques.
Proposing several heuristic algorithms facilitated by the topological sorting.

Main Results:

The task planning optimization problem is proven to be NP-hard.
A lower bound was established to assess solution proximity to the optimum.
The proposed heuristic algorithms demonstrated rapid convergence to satisfactory solutions.

Conclusions:

The developed heuristic algorithms provide efficient and effective solutions for the vehicle task planning problem with precedence constraints.
These algorithms outperform popular genetic algorithms in numerical experiments.