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Faculty Dr Edukondalu Chappidi

Dr Edukondalu Chappidi

Assistant Professor

Department of Computer Science and Engineering

Contact Details

edukondalu.c@srmap.edu.in

Office Location

Homi J Bhabha Block, Level 2, Cubicle No: 25

Education

2023
University of Hyderabad
India
2010
M.E.
Indian Institute of Science, Bengaluru
India
2008
B.E.
Osmania University College of Engineering

Experience

  • 2023 - 24 – Associate Professor – BVRITH College of Engg for Women, Hyderabad
  • 2014 - 2015 – Project Associate – Indian Institute of Science, Bengaluru
  • 2010 - 2014 – Member Technical Staff – NetApp India Pvt Ltd, Bengaluru

Research Interest

  • My research interest is focused in investigation and development of heuristic, metaheuristic & hyper-heuristic techniques for combinatorial optimization problems.
  • To efficiently solve real world problems using machine learning techniques.

Awards

  • 2002 – Prathibha Award – Government of Andhra Pradesh
  • 2008-10 – MHRD Scholarship - Government of India
  • 2008 – All India Rank 77 – GATE(CS), 2008
  • 2016 – Assistant Professorship – UGC-NET
  • 2020 – Outstanding Paper Award – Indian Institute of Technology, Indore
  • 2023 – ATAL FDP – AICTE, Government of India

Memberships

No data available

Publications

  • Solution of reliable p-median problem with at-facility service using multi-start hyper-heuristic approaches

    Dr Edukondalu Chappidi, Alok Singh

    Source Title: Applied Intelligence, Quartile: Q1, DOI Link

    View abstract ⏷

    This paper presents two hyper-heuristic approaches for solving a facility location problem called reliable p-median problem with at facility service (RpMF). In RpMF, service is provided to customers at the facility locations and it is closely related to the p-median problem. p-median problem is concerned with locating p-facilities while minimizing the total distance traveled by the customers to the corresponding nearest facilities and it is an -hard problem. But according to the p-median problem, it doesn’t consider the possibility of facility failures. On the other hand, RpMF assumes that facilities can fail and the customers assigned to that facility do not know about the facility failure till they reach the facility for service. So, the customers have to travel from failed facilities to other functioning facilities to receive service. RpMF deals with locating p facilities to minimize the cost of serving the customers while considering facility failures. We have proposed two multi-start hyper-heuristic based approaches that are based on greedy and random selection mechanisms to solve the RpMF. The solutions obtained through hyper-heuristics are improved further via a local search. The two proposed hyper-heuristic approaches are evaluated on 405 RpMF benchmark instances from the literature. Experimental results prove the effectiveness of the proposed approaches in comparison to the state-of-the-art approaches available in literature for the RpMF

Patents

Projects

Scholars

Doctoral Scholars

  • Mr Pavan Kumar Ventrapragada

Interests

  • Artificial Intelligence
  • Machine Learning

Thought Leaderships

There are no Thought Leaderships associated with this faculty.

Top Achievements

Education
2008
B.E.
Osmania University College of Engineering
2010
M.E.
Indian Institute of Science, Bengaluru
India
2023
University of Hyderabad
India
Experience
  • 2023 - 24 – Associate Professor – BVRITH College of Engg for Women, Hyderabad
  • 2014 - 2015 – Project Associate – Indian Institute of Science, Bengaluru
  • 2010 - 2014 – Member Technical Staff – NetApp India Pvt Ltd, Bengaluru
Research Interests
  • My research interest is focused in investigation and development of heuristic, metaheuristic & hyper-heuristic techniques for combinatorial optimization problems.
  • To efficiently solve real world problems using machine learning techniques.
Awards & Fellowships
  • 2002 – Prathibha Award – Government of Andhra Pradesh
  • 2008-10 – MHRD Scholarship - Government of India
  • 2008 – All India Rank 77 – GATE(CS), 2008
  • 2016 – Assistant Professorship – UGC-NET
  • 2020 – Outstanding Paper Award – Indian Institute of Technology, Indore
  • 2023 – ATAL FDP – AICTE, Government of India
Memberships
No data available
Publications
  • Solution of reliable p-median problem with at-facility service using multi-start hyper-heuristic approaches

    Dr Edukondalu Chappidi, Alok Singh

    Source Title: Applied Intelligence, Quartile: Q1, DOI Link

    View abstract ⏷

    This paper presents two hyper-heuristic approaches for solving a facility location problem called reliable p-median problem with at facility service (RpMF). In RpMF, service is provided to customers at the facility locations and it is closely related to the p-median problem. p-median problem is concerned with locating p-facilities while minimizing the total distance traveled by the customers to the corresponding nearest facilities and it is an -hard problem. But according to the p-median problem, it doesn’t consider the possibility of facility failures. On the other hand, RpMF assumes that facilities can fail and the customers assigned to that facility do not know about the facility failure till they reach the facility for service. So, the customers have to travel from failed facilities to other functioning facilities to receive service. RpMF deals with locating p facilities to minimize the cost of serving the customers while considering facility failures. We have proposed two multi-start hyper-heuristic based approaches that are based on greedy and random selection mechanisms to solve the RpMF. The solutions obtained through hyper-heuristics are improved further via a local search. The two proposed hyper-heuristic approaches are evaluated on 405 RpMF benchmark instances from the literature. Experimental results prove the effectiveness of the proposed approaches in comparison to the state-of-the-art approaches available in literature for the RpMF
Contact Details

edukondalu.c@srmap.edu.in

Scholars

Doctoral Scholars

  • Mr Pavan Kumar Ventrapragada

Interests

  • Artificial Intelligence
  • Machine Learning

Education
2008
B.E.
Osmania University College of Engineering
2010
M.E.
Indian Institute of Science, Bengaluru
India
2023
University of Hyderabad
India
Experience
  • 2023 - 24 – Associate Professor – BVRITH College of Engg for Women, Hyderabad
  • 2014 - 2015 – Project Associate – Indian Institute of Science, Bengaluru
  • 2010 - 2014 – Member Technical Staff – NetApp India Pvt Ltd, Bengaluru
Research Interests
  • My research interest is focused in investigation and development of heuristic, metaheuristic & hyper-heuristic techniques for combinatorial optimization problems.
  • To efficiently solve real world problems using machine learning techniques.
Awards & Fellowships
  • 2002 – Prathibha Award – Government of Andhra Pradesh
  • 2008-10 – MHRD Scholarship - Government of India
  • 2008 – All India Rank 77 – GATE(CS), 2008
  • 2016 – Assistant Professorship – UGC-NET
  • 2020 – Outstanding Paper Award – Indian Institute of Technology, Indore
  • 2023 – ATAL FDP – AICTE, Government of India
Memberships
No data available
Publications
  • Solution of reliable p-median problem with at-facility service using multi-start hyper-heuristic approaches

    Dr Edukondalu Chappidi, Alok Singh

    Source Title: Applied Intelligence, Quartile: Q1, DOI Link

    View abstract ⏷

    This paper presents two hyper-heuristic approaches for solving a facility location problem called reliable p-median problem with at facility service (RpMF). In RpMF, service is provided to customers at the facility locations and it is closely related to the p-median problem. p-median problem is concerned with locating p-facilities while minimizing the total distance traveled by the customers to the corresponding nearest facilities and it is an -hard problem. But according to the p-median problem, it doesn’t consider the possibility of facility failures. On the other hand, RpMF assumes that facilities can fail and the customers assigned to that facility do not know about the facility failure till they reach the facility for service. So, the customers have to travel from failed facilities to other functioning facilities to receive service. RpMF deals with locating p facilities to minimize the cost of serving the customers while considering facility failures. We have proposed two multi-start hyper-heuristic based approaches that are based on greedy and random selection mechanisms to solve the RpMF. The solutions obtained through hyper-heuristics are improved further via a local search. The two proposed hyper-heuristic approaches are evaluated on 405 RpMF benchmark instances from the literature. Experimental results prove the effectiveness of the proposed approaches in comparison to the state-of-the-art approaches available in literature for the RpMF
Contact Details

edukondalu.c@srmap.edu.in

Scholars

Doctoral Scholars

  • Mr Pavan Kumar Ventrapragada