Abstract
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 NPhard in nature; hence, finding an optimal solution is often difficult, demanding highly efficient techniques. Many exact and heuristic algorithms have been proposed out of these challenging and practically relevant optimization problems including those that draw inspiration from nature. The aim of this special issue is to showcase how heuristics, operations research, computational intelligence, and other optimization techniques have been successfully applied to solve real-world industrial optimization problems. Researchers were invited to contribute original research and review articles that explore, model, and solve real life optimization problems in various fields. The special issue attracted many high quality papers of which few were selected based on set quality criteria after rigorous peerreview, revision, and editorial processes. The published high quality papers cover various applications of optimization to varying problems especially in the industries including engineering, inventory, logistics, and marketing, scheduling, resource, and transportation planning, computing and ICT, water and gas resource management, and data mining. Most papers dwell on modeling of real-world industrial problems, innovative optimization technique for solving real-world problems including heuristics, finite methods, operation research techniques, intelligent algorithms, and agent-based methods. Many of the papers propose innovative techniques for solving specified problem while others present improved methods compared with existing ones. Here, we present a summary of the published papers categorized according to the problem domain addressed.
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