Find Jobs
Hire Freelancers

Biologically-inspired Techniques for Solving Constrained Multi-objective Optimization Problems

$30-250 USD

Closed
Posted over 10 years ago

$30-250 USD

Paid on delivery
Description : Most real-world problems involve complex optimization with various conflicting specifications, which cannot be solved without advanced techniques. In addition, most of these problems are also commonly imbued by linear/nonlinear equality/inequality constraints, which only make them more difficult to solve, even by most renowned numerical optimization techniques. Hence, the major goal in solving this problem is to obtain set of feasible tradeoff solutions that satisfy the various optimization goals. The past decades have seen the development of powerful optimization techniques which draws inspiration from nature. Among those are a group of stochastic optimization algorithms inspired by Darwin's theory of evolution, collectively known as Evolutionary Algorithms (EAs). EAs have shown considerable success in locating the global optimum solution of optimization problems that may often be characterized by high dimensional, non-separable, multi-modal, constrained, and discontinuous/non-differentiable fitness landscape. In this project, we will examine and propose new constraint handling techniques that can be embedded into evolutionary algorithms. Particularly, a meta-Lamarckian approach will be explored to learn adaptively from the problem the best manner of constraint handling during an evolutionary optimization. Deliverables: Part 1: -Path planning for robots. i.e. Unmanned Vehicles. (Unmanned aerial vehicles, unmanned ground vehicles). - In 2D, using one of evolutionary algorithm concept. (Genetic algorithm). -Single-objective Optimization (Shortest Path). - Solve some constraints. E.g. Minimum collision Part 2: Extension of path one. -Path planning for robots. i.e. Unmanned Vehicles. (Unmanned aerial vehicles, unmanned ground vehicles). -In 3D, with the invention of new algorithm or concept.(hybrid of two types of evolutionary algorithm or compensation of drawbacks of any one concept. ) -Multi-Objective optimization. (More than one factor- speed, shortest path, etc) - Solve some constraints. (E.g. Minimum collision.) Platform : Python. Please give description of each class/methods as comments. If you are getting distance from user for different routes to choose the best one, or any other user input, please provide a ‘read me’ text on how to use the system.
Project ID: 4889523

About the project

2 proposals
Remote project
Active 10 yrs ago

Looking to make some money?

Benefits of bidding on Freelancer

Set your budget and timeframe
Get paid for your work
Outline your proposal
It's free to sign up and bid on jobs
2 freelancers are bidding on average $224 USD for this job
User Avatar
hi... i can do this.
$222 USD in 3 days
0.0 (0 reviews)
0.0
0.0
User Avatar
Hi, We have expert in-house team of Python programmers. Please check private message.
$226 USD in 7 days
0.0 (0 reviews)
0.0
0.0

About the client

Flag of UNITED STATES
Sunnyvale, United States
5.0
97
Payment method verified
Member since Jul 24, 2012

Client Verification

Thanks! We’ve emailed you a link to claim your free credit.
Something went wrong while sending your email. Please try again.
Registered Users Total Jobs Posted
Freelancer ® is a registered Trademark of Freelancer Technology Pty Limited (ACN 142 189 759)
Copyright © 2024 Freelancer Technology Pty Limited (ACN 142 189 759)
Loading preview
Permission granted for Geolocation.
Your login session has expired and you have been logged out. Please log in again.