Search Results for author: M. A. Hakim Newton

Found 8 papers, 0 papers with code

Solving Travelling Thief Problems using Coordination Based Methods

no code implementations11 Oct 2023 Majid Namazi, M. A. Hakim Newton, Conrad Sanderson, Abdul Sattar

In TTP, city selection and item selection decisions need close coordination since the thief's travelling speed depends on the knapsack's weight and the order of visiting cities affects the order of item collection.

Surrogate Assisted Optimisation for Travelling Thief Problems

no code implementations14 May 2020 Majid Namazi, Conrad Sanderson, M. A. Hakim Newton, Abdul Sattar

The TSP solution (cyclic tour) is typically changed in a deterministic way, while changes to the KP solution typically involve a random search, effectively resulting in a quasi-meandering exploration of the TTP solution space.

A Cooperative Coordination Solver for Travelling Thief Problems

no code implementations8 Nov 2019 Majid Namazi, Conrad Sanderson, M. A. Hakim Newton, Abdul Sattar

A thief performs a cyclic tour through a set of cities, and pursuant to a collection plan, collects a subset of items into a rented knapsack with finite capacity.

Toxicity Prediction by Multimodal Deep Learning

no code implementations19 Jul 2019 Abdul Karim, Jaspreet Singh, Avinash Mishra, Abdollah Dehzangi, M. A. Hakim Newton, Abdul Sattar

Prediction of toxicity levels of chemical compounds is an important issue in Quantitative Structure-Activity Relationship (QSAR) modeling.

Multimodal Deep Learning

Efficient Toxicity Prediction via Simple Features Using Shallow Neural Networks and Decision Trees

no code implementations26 Jan 2019 Abdul Karim, Avinash Mishra, M. A. Hakim Newton, Abdul Sattar

Lately, it achieved significant progress in accuracy but using a huge set of features, implementing a complex blackbox technique such as a deep neural network, and exploiting enormous computational resources.

Diversified Late Acceptance Search

no code implementations25 Jun 2018 Majid Namazi, Conrad Sanderson, M. A. Hakim Newton, M. M. A. Polash, Abdul Sattar

The well-known Late Acceptance Hill Climbing (LAHC) search aims to overcome the main downside of traditional Hill Climbing (HC) search, which is often quickly trapped in a local optimum due to strictly accepting only non-worsening moves within each iteration.

Mixing Energy Models in Genetic Algorithms for On-Lattice Protein Structure Prediction

no code implementations15 Nov 2013 Mahmood A. Rashid, M. A. Hakim Newton, Md. Tamjidul Hoque, Abdul Sattar

In this paper, we develop a genetic algorithm that mainly uses a high resolution energy model for protein structure evaluation but uses a low resolution HP energy model in focussing the search towards exploring structures that have hydrophobic cores.

Protein Structure Prediction

A Hybrid Local Search for Simplified Protein Structure Prediction

no code implementations31 Oct 2013 Swakkhar Shatabda, M. A. Hakim Newton, Duc Nghia Pham, Abdul Sattar

Protein structure prediction based on Hydrophobic-Polar energy model essentially becomes searching for a conformation having a compact hydrophobic core at the center.

Protein Structure Prediction

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