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Handbook of Optimization 2023 : Handbook of Formal Optimization Methods | |||||||||||||||
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Call For Papers | |||||||||||||||
Call For Chapters
‘Handbook of Formal Optimization Methods’ - SPRINGER This is an open invitation to submit a chapter to one of the sections of the handbook. The chapter is expected to include background/literature review, method description including mathematical formulation, illustrations, problem(s) and application(s) solved, results and discussions, flowcharts/pseudocodes, etc. Aim and Scope Optimization carries great significance in both human affairs and the laws of nature. It refers to a positive and intrinsically human concept of minimization or maximization to achieve the best or most favorable outcome from a given situation. Besides, as the resources are becoming scarce, there is a need to develop new methods and techniques and modify the existing ones which will make the systems extract maximum from minimum use of these resources, i.e., maximum utilization of available resources with minimum investment or cost of any kind. The resources could be any, such as land, materials, machines, personnel, skills, time, etc. The handbook aims at discussing background/literature review, optimization method description including mathematical formulation, illustrations, problems and application(s), results and critical discussions, flowcharts/pseudocodes, etc. The handbook is expected to serve as a complete reference discussing a wide aspect of optimization methods. The handbook sections are given below. Section I: Mathematical Optimization/Programming Section II: Bayesian Optimization Section III: Evolutionary Optimization-based Methods Section IV: Bio-inspired Optimization Section V: Swarm-based Optimization Section VI: Physics-based Optimization Section VII: Socio-inspired based Optimization Section VIII: Machine Learning Section IX: Neural Networks and Deep Learning Section X: Multi/Many-objective Optimization Section XI: Hybrid Optimization Methods Section XII: Heuristics in Optimization Section XIII: Goal Programming Problems and Methods Section XIV: Combinatorial Optimization Section XV: Genetic Algorithms and Applications Section XVI: Engineering Optimization Section XVII: Optimization in Management Section XVIII: Optimization in Manufacturing Processes Section XIX: Constraint Handling in Optimization Methods Important Dates: Chapter Proposal Jul 31, 2022 Full Chapter Submission: Sep 30, 2022 Chapter Review Notification: Oct 30, 2022 Revised Chapter Due: Nov 30, 2022 Final Acceptance: Dec 15, 2022 Expected Publication Date: Jan 30, 2023 Editors: Prof. Anand J Kulkarni, MIT World Peace University Prof. Amir H Gandomi, University of Technology Sydney If interested, please email a tentative title, author names, and affiliations to anand.j.kulkarni@mitwpu.edu.in by July 31 |
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