This book analyzes the underlying theoretical principles of multi-objective linear programming problems with multi-choice parameters. It studies transportation problems on the same domain with extension to fuzzy stochastic criteria, and offers insights into sensitivity analysis through symmetric duality and complementarity using non-convex programming. These analytical presentations provide ample scope for researchers to contemplate real-world problems with an innovative vision. The formulation, analysis and solution procedures on inventory control models in the book use both deterministic and fuzzy parameters, and provide novel optimal inventory policies. The book discusses a wide range of optimal operational techniques for policy makers, government and private agencies in the fields of e-governance and agricultural crop insurance, which are crucial for developing countries. The recommendations address the gaps and remedies in various schemes that influence decision-making in the context of the economic development of such countries.

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. Presents a new model based on an unreliable server, wherein, the convergence analysis is done using nature-inspired algorithms. Discusses PCM thermal energy storage system, wherein, response surface methodology (RSM) algorithm is used. 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.

This book analyzes the underlying theoretical principles of multi-objective linear programming problems with multi-choice parameters. It studies transportation problems on the same domain with extension to fuzzy stochastic criteria, and offers insights into sensitivity analysis through symmetric duality and complementarity using non-convex programming. These analytical presentations provide ample scope for researchers to contemplate real-world problems with an innovative vision. The formulation, analysis and solution procedures on inventory control models in the book use both deterministic and fuzzy parameters, and provide novel optimal inventory policies. The book discusses a wide range of optimal operational techniques for policy makers, government and private agencies in the fields of e-governance and agricultural crop insurance, which are crucial for developing countries. The recommendations address the gaps and remedies in various schemes that influence decision-making in the context of the economic development of such countries.