Title :
Research on multi-objective location-routing problem (MLRP) with random analysis for regional distribution
Author_Institution :
Sch. of Econ. & Finance, HuaQiao Univ., Quanzhou, China
Abstract :
The location of the distribution facilities and the vehicles from these facilities are interdependent in many distribution systems. Such a concept recognizes the interdependence; attempts to integrate these two decisions have been limited. Multi-objective location-routing problem (MLRP) is combined the facility location and the vehicle routing decision and satisfied the different objectives. Due to the problem complexity, simultaneous solution methods are limited, which exits in different objectives with conflicts in functions satisfied. Two kinds of optimal mathematical models are proposed for the solution of MLRP. The three methods have been emphatically developed for MLRP. Multi-objective genetic algorithm (MGA) is introduced to solving MLRP based on Pareto. MGA architecture makes it possible to search the solution space efficiently, which provides a path for searching the solution with two-objective LRP. At Last the practical prove is given by random analysis for regional distribution with nine cities.
Keywords :
Pareto optimisation; facility location; genetic algorithms; goods distribution; MLRP; Pareto solution; distribution facility location; multiobjective genetic algorithm; multiobjective location routing problem; optimal mathematical model; random analysis; regional distribution; vehicle routing decision; Complexity theory; Genetic algorithms; Logistics; Mathematical model; Optimization; Reliability; Vehicles; Pareto solution; exact algorithm; genetic algorithm (GA); heuristic; location routing problem (LRP); multi-objective optimization; random analysis; regional distribution; satisfactory solution; systems reliability;
Conference_Titel :
Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
Conference_Location :
Harbin, Heilongjiang, China
Print_ISBN :
978-1-61284-087-1
DOI :
10.1109/EMEIT.2011.6022980