Advances in Operational Researches
Jovan Pehcevski
9781774691755
389 pages
Arcler Education Inc
Overview
This book covers different topics related to advanced operational researches, including optimization and linear programming, graph-based techniques and route planning, operations research in logistics problems, and methods for resource allocation.
Section 1 focuses on optimization and linear programming, describing a new approach for solving linear fractional programming problems with duality concept, a particle swarm optimization algorithm for solving pricing and lead time quotation in a dual-channel supply chain with multiple customer classes, inverting the multiple-assisting tool network problem to solve for optimality, a dynamic active-set method for linear programming, and the sliding gradient algorithm for linear programming.
Section 2 focuses on graph-based techniques and route planning, describing route optimization of electric vehicle considering soft time windows and two ways of power replenishment, the route planning on campus bus in a University, integrating origin-destination survey and stochastic user equilibrium as a case study for route relocation, and research of UAV flight planning parameters.
Section 3 focuses on operations research in logistics problems, describing optimization of urban rail transportation in emerging countries using operational research techniques, a review on strategic, tactical and operational decision planning in reverse logistics of green supply chain network design, research on agri-food cold chain logistics management system, a use case of sea-port operational efficiency by an evaluation of five Asian ports using stochastic frontier production function model, and the design of urban traffic in Ferizaj through operational research.
Section 4 focuses on methods for resource allocation, describing application of the two non-zero component lemma in resource allocation, energy efficient non-cooperative methods for resource allocation in cognitive radio networks, an alternative interpretation of mixed strategies in n-person normal form games via resource allocation, and a dynamic optimization technique for resource allocation problems in a production company.
Author Bio
Jovan obtained his PhD in Computer Science from RMIT University in Melbourne, Australia in 2007. His research interests include big data, business intelligence and predictive analytics, data and information science, information retrieval, XML, web services and service-oriented architectures, and relational and NoSQL database systems. He has published over 30 journal and conference papers and he also serves as a journal and conference reviewer. He is currently working as a Dean and Associate Professor at European University in Skopje, Macedonia.
