LO 2014 - Special Session on Logistics and optimization
Date2014-06-03 - 2014-06-05
Deadline2014-02-15
VenueMoscow, Russia
Keywords
Websitehttps://itqm2014.hse.ru
- 2025 International Conference on Logistics and Supply Chain Management
- 11th International Conference on Innovation and Industrial Logistics (ICIIL 2025)
- 2025 International Conference on Logistics and Supply Chain Management (CoLSCM 2025)
- 【Tech Science Press】【SCI-Expanded EI检索】【快速SCOPUS检索】期刊征稿.SCI 专刊 (Special Issue) 长期征稿
- Short Course on Zero-Emission Freight Transport and Logistics
Topics/Call fo Papers
Prof. Panos M. Pardalos, ppardalos-AT-hse.ru (University of Florida)
Leading Research Fellow Mikhail Batsyn, mbatsyn-AT-hse.ru (Laboratory of Algorithms and Technologies for Network Analysis, HSE)
The main goal of this session is to consider real-life logistics and optimization problems and present modern algorithms for solving such problems. These problems include, but not limited to: rich vehicle routing problems, warehouse optimization problems, manufacturing optimization problems, production scheduling problems. The main feature of real-life optimization problems is a large number of variables and constraints in its mathematical programming formulations. In most cases this makes it impossible to find a global optimum of a real-life optimization problem. Fortunately, in practice it is usually enough to find a solution which is significantly better than a solution which can be obtained by hand applying some simple greedy considerations. Due to the fast development of modern computers and meta-heuristic algorithms nowadays it is possible to build millions of heuristic solutions in reasonable time intensively and diversely exploring the solution space. This helps to find very good solutions in practice.
Leading Research Fellow Mikhail Batsyn, mbatsyn-AT-hse.ru (Laboratory of Algorithms and Technologies for Network Analysis, HSE)
The main goal of this session is to consider real-life logistics and optimization problems and present modern algorithms for solving such problems. These problems include, but not limited to: rich vehicle routing problems, warehouse optimization problems, manufacturing optimization problems, production scheduling problems. The main feature of real-life optimization problems is a large number of variables and constraints in its mathematical programming formulations. In most cases this makes it impossible to find a global optimum of a real-life optimization problem. Fortunately, in practice it is usually enough to find a solution which is significantly better than a solution which can be obtained by hand applying some simple greedy considerations. Due to the fast development of modern computers and meta-heuristic algorithms nowadays it is possible to build millions of heuristic solutions in reasonable time intensively and diversely exploring the solution space. This helps to find very good solutions in practice.
Other CFPs
Last modified: 2014-01-18 16:12:22