S. Gupta

发表

Performance of Grey Wolf Optimizer on large scale problems

K. Deep, S. Gupta, 2017 .

Algorithmic challenges in the theory of queueing networks

D. Gamarnik, S. Gupta, 2011 .

Fairness in Air Traffic Flow Management ∗

Dimitris Bertsimas, Shubham Gupta, D. Bertsimas, 2009 .

Discrete Weighted Hardy Inequality in 1-D

S. Gupta, 2021, Journal of Mathematical Analysis and Applications.

Enhanced leadership-inspired grey wolf optimizer for global optimization problems

K. Deep, S. Gupta, Kusum Deep, 2019, Engineering with Computers.

A Tractable Optimization Framework for Air Traffic Flow Management Addressing Fairness, Collaboration and Stochasticity

Shubham Gupta, S. Gupta, 2012 .

A novel Random Walk Grey Wolf Optimizer

Kusum Deep, Shubham Gupta, K. Deep, 2019, Swarm Evol. Comput..

An Efficient Grey Wolf Optimizer with Opposition-Based Learning and Chaotic Local Search for Integer and Mixed-Integer Optimization Problems

Kusum Deep, Shubham Gupta, K. Deep, 2019, Arabian Journal for Science and Engineering.

Comparison of metaheuristic optimization algorithms for solving constrained mechanical design optimization problems

Sadiq M. Sait, Seyed Mohammad Mirjalili, Hammoudi Abderazek, 2021, Expert Syst. Appl..

An efficient equilibrium optimizer with mutation strategy for numerical optimization

Kusum Deep, Seyedali Mirjalili, Shubham Gupta, 2020, Appl. Soft Comput..

Fairness and Collaboration in Network Air Traffic Flow Management: An Optimization Approach

Dimitris Bertsimas, Shubham Gupta, D. Bertsimas, 2016, Transp. Sci..

A memory-based Grey Wolf Optimizer for global optimization tasks

Kusum Deep, Shubham Gupta, K. Deep, 2020, Appl. Soft Comput..

Enhanced leadership-inspired grey wolf optimizer for global optimization problems

Kusum Deep, Shubham Gupta, K. Deep, 2019, Engineering with Computers.

A novel hybrid sine cosine algorithm for global optimization and its application to train multilayer perceptrons

K. Deep, S. Gupta, Kusum Deep, 2019, Applied Intelligence.

Hybrid sine cosine artificial bee colony algorithm for global optimization and image segmentation

K. Deep, S. Gupta, 2019, Neural Computing and Applications.

Opposition-based learning Harris hawks optimization with advanced transition rules: principles and analysis

Kusum Deep, Hossein Moayedi, Shubham Gupta, 2020, Expert Syst. Appl..

Harmonized salp chain-built optimization

Kusum Deep, Hossein Moayedi, Huiling Chen, 2019, Engineering with Computers.

Sine cosine grey wolf optimizer to solve engineering design problems

Kusum Deep, Hossein Moayedi, Loke Kok Foong, 2020, Engineering with Computers.

A hybrid self-adaptive sine cosine algorithm with opposition based learning

Kusum Deep, Shubham Gupta, K. Deep, 2019, Expert Syst. Appl..

Improved sine cosine algorithm with crossover scheme for global optimization

Kusum Deep, Shubham Gupta, K. Deep, 2019, Knowl. Based Syst..

A novel hybrid sine cosine algorithm for global optimization and its application to train multilayer perceptrons

Kusum Deep, Shubham Gupta, K. Deep, 2019, Applied Intelligence.

Cauchy Grey Wolf Optimiser for continuous optimisation problems

Kusum Deep, Shubham Gupta, K. Deep, 2018, J. Exp. Theor. Artif. Intell..

A modified Sine Cosine Algorithm with novel transition parameter and mutation operator for global optimization

Kusum Deep, Joong Hoon Kim, Seyedali Mirjalili, 2020, Expert Syst. Appl..

A memory guided sine cosine algorithm for global optimization

Andries Petrus Engelbrecht, Kusum Deep, Shubham Gupta, 2020, Eng. Appl. Artif. Intell..

An Efficient Grey Wolf Optimizer with Opposition-Based Learning and Chaotic Local Search for Integer and Mixed-Integer Optimization Problems

K. Deep, S. Gupta, Kusum Deep, 2019, Arabian Journal for Science and Engineering.

An opposition-based chaotic Grey Wolf Optimizer for global optimisation tasks

Kusum Deep, Shubham Gupta, K. Deep, 2018, J. Exp. Theor. Artif. Intell..

Random walk grey wolf optimizer for constrained engineering optimization problems

Kusum Deep, Shubham Gupta, K. Deep, 2018, Comput. Intell..

An aggregative learning gravitational search algorithm with self-adaptive gravitational constants

Jiujun Cheng, Shangce Gao, Shubham Gupta, 2020, Expert Syst. Appl..

Reliability-Based Optimization Using Evolutionary Algorithms

Kalyanmoy Deb, Jürgen Branke, Shubham Gupta, 2009, IEEE Transactions on Evolutionary Computation.

Reliability-Redundancy Allocation Using Random Walk Gray Wolf Optimizer

Kusum Deep, Shubham Gupta, Assif Assad, 2018, SocProS.

Enhanced harmony search algorithm with non-linear control parameters for global optimization and engineering design problems

Shubham Gupta, S. Gupta, 2021, Engineering with Computers.

Efficient Initialization of Particle Swarm Optimization Using Low Discrepancy Sequence

Himanshu Gupta, Shubham Kumar Gupta, Pranshu Nayak, 2016, SoCPaR.

Enhanced sine cosine algorithm with crossover: A comparative study and empirical analysis

S. Gupta, 2022, Expert Syst. Appl..

Dynamic resource allocation: A flexible and tractable modeling framework

Dimitris Bertsimas, Shubham Gupta, Guglielmo Lulli, 2014, Eur. J. Oper. Res..

How effective is Black Hole Algorithm?

Arpit Gupta, Himanshu Gupta, Shubham Kumar Gupta, 2016, 2016 2nd International Conference on Contemporary Computing and Informatics (IC3I).

Order Reduction of Linear Time Invariant System using Particle Swarm Optimization

Shubham Kumar Gupta, Tanmay Shrivastava, Kuldeep Rathore, 2018, 2018 2nd IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES).

Hybrid Grey Wolf Optimizer with Mutation Operator

Kusum Deep, Shubham Gupta, S. Gupta, 2018, SocProS.

Digital Marketing Effectiveness Using Incrementality

Shubham Gupta, Sneha Chokshi, S. Gupta, 2020 .

A 3-Approximation for Facility Location with Uniform Capacities

Ankit Aggarwal, Naveen Garg, Shubham Gupta, 2010, IPCO.