Jyotiranjan Nayak – författare

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 algorithmsDiscusses the optimization techniques used in transportation problems, timetable problems, and optimal/dynamic pricing in inventory controlHighlights single and multi-objective optimization problems using pentagonal fuzzy numbersIllustrates profit maximization inventory model for non-instantaneous deteriorating items with imprecise costsShowcases nature-inspired algorithms such as particle swarm optimization, genetic algorithm, bat algorithm, and cuckoo search algorithmThe 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.

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 algorithmsDiscusses the optimization techniques used in transportation problems, timetable problems, and optimal/dynamic pricing in inventory controlHighlights single and multi-objective optimization problems using pentagonal fuzzy numbersIllustrates profit maximization inventory model for non-instantaneous deteriorating items with imprecise costsShowcases nature-inspired algorithms such as particle swarm optimization, genetic algorithm, bat algorithm, and cuckoo search algorithmThe 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 covers cutting-edge research that includes operations research and decision sciences. It examines finite queueing systems with unreliable service provisioning and feedback strategies. Retrial queueing systems with customer feedback and individual abandonments are dynamically investigated. The book presents fuzzy logic approaches for multi-objective transportation problems. Multi-objective programming methodologies effectively deal with problems associated with catastrophe management. Healthcare decision-making under uncertain contexts deserves special attention. Inventory models combine trade credit financing with credit-linked demand functions. Financial risk analysis, business estimation, and bilevel portfolio optimization strategies are thoroughly investigated.Features:Delves into practical approaches to operational research concerns, offering frameworks that address real-world scenarios.Introduces new techniques and strategies for problem-solving, involving the development of physical scenarios, effective algorithms, and straightforward implementation.Discusses topics such as inventory control models, RMS optimization, fuzzy optimization with unique membership functions, and traffic simulation for telecommunication networks.Covers mathematical perspectives, such as variable costs, perishable and non-perishable products for consumers, fuzzy decision variables, and constraint qualifications.Presents an in-depth analysis of the latest developments shaping the field of operations research.It is primarily written for graduate students and academic researchers in operations research, industrial engineering, systems engineering, production engineering, manufacturing engineering, mathematics, and quality control.

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.