Modeling and Applications in Operations Research

The text envisages novel optimization methods that significantly impact real-life problems, starting from inventory control to economic decision-making. It discusses topics such as inventory control, queueing models, timetable scheduling, fuzzy optimization, and the Knapsack problem. The book’s content encompass the
following key aspects:

Presents a new model based on an unreliable server, wherein the convergence analysis is done using nature-inspired algorithms.
Discusses the optimization techniques used in transportation problems, timetable problems, and optimal/dynamic pricing in inventory control.
Highlights single and multi-objective optimization problems using pentagonal fuzzy numbers.
Illustrates profit maximization inventory model for non-instantaneous deteriorating items with imprecise costs.
Showcases nature-inspired algorithms such as particle swarm optimization, genetic algorithm, bat algorithm, and cuckoo search algorithm.

The text covers multi-disciplinary real-time problems such as fuzzy optimization of transportation problems, inventory control with dynamic pricing, timetable problem with ant colony optimization, knapsack problem, queueing modeling using the nature-inspired algorithm, and multi-objective fuzzy linear programming. It showcases a comparative analysis for studying various combinations of system design parameters and default cost elements. It will serve as an ideal reference text for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, production engineering, mechanical engineering, and mathematics.