Journal of Applied Mathematics

Mathematical Modeling and Optimization of Industrial Problems


Lead Editor

1University of the Witwatersrand, Johannesburg, South Africa

2University of KwaZulu-Natal, Durban, South Africa

3University of Jos, Jos, Nigeria

4University of Cape Town, Cape Town, South Africa

Mathematical Modeling and Optimization of Industrial Problems


Optimization plays an ever-increasing role in mathematics, economics, engineering, health sciences, management, life sciences, and almost all other fields of study. Many optimization problems exist in the real world including space planning, networking, logistic management, financial planning, and risk management. These problems are NP-hard in nature; hence, finding an optimal solution is often difficult, demanding highly efficient techniques. Many exact and heuristics algorithms have been proposed out of these challenging and practically relevant optimization problems including those that draw inspiration from nature.

This special issue aims at showcasing how heuristics, operations research, computational intelligence, and other optimization techniques have been successfully applied to solve real-world industrial optimization problems. Researchers are invited to contribute original research and review articles that explore, model, and solve real life optimization problems in various fields. Of interest are articles on heuristic approach to solve these problems with emphasis on computational intelligence techniques. Optimization techniques applied to real-world problems including blood assignments, call-centre scheduling, personnel scheduling, timetabling, irrigation scheduling, crop planning, sport scheduling, image processing, engineering design, network management, unconstrained global optimization problems, and many others are invited.

Potential topics include, but are not limited to:

  • Modeling of real-world industrial problems and applications
  • Finite methods for solving industrial problems
  • Innovative heuristic, metaheuristic, hyperheuristic and math-heuristic solutions to real-world problems
  • Benchmarking of real-world problems
  • New and improved algorithms for existing optimization problems
  • Intelligence algorithms and solutions to real-world problems
  • Multiagent based techniques for real-world problems
  • Operations research techniques applied to problems in developing countries
Journal of Applied Mathematics
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Acceptance rate17%
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