Improvement and Applications of Heuristic Algorithms in Practical Engineering Management Problems
International Journal of Management Science and Engineering Management
Many optimization and decision making problems in Engineering Management are complex and nonlinear, can be challenging to be solved using traditional methods. In many cases, metaheurisitc algorithms can be an effective alternative in engineering applications. The most popular algorithms are Genetic Algorithm, Particle Swarm Optimization algorithm, Tabu Algorithm etc.
In the background of big data and artificial intelligence era, the metaheurisitc algorithms are in significantly greater need. The proposed algorithms need to be improved in terms of efficiency and fitting specific problems. More new algorithms are also being proposed.
In this thematic collection, you will see the successful improvement and applications of heuristic algorithms in practical Engineering Management problems, such as design and network engineering problems, economic dispatch problems, the weighted set cover problems, land layout optimization of cities, and optimal power flow design problems. Some progress of proposing new hybrid matheuristic optimization algorithms, and improvements of frequently-used algorithms can also be found in this thematic collection.
All articles are available to view and access until 31 December 2019.
|A new hybrid matheuristic optimization algorithm for solving design and network engineering problems||G. Chagwiza, B. C. Jones, S. D. Hove-Musekwa, S. Mtisi|
|An heuristic genetic algorithm for strategic university tuition planning and workload balancing||Eero Immonen & Ari Putkonen|
|The exchange market algorithm with smart searching for solving economic dispatch problems||Naser Ghorbani & Ebrahim Babaei|
|Efficient network algorithms for two special cases of the weighted set cover problem||Javad Tayyebi, Abumoslem Mohammadi|
|A game theory based land layout optimization of cities using genetic algorithm||Parth Paritosh, Bhaben Kalita, Deepak Sharma|
|Improvement optimal power flow solution under loading margin stability using new partitioning whale algorithm||Belkacem Mahdad|