ABSTRACT
Coordination is essential for improving supply chain performance, and one of the most critical factors in achieving the coordination of a supply chain is the integrated research of production and distribution. In this paper, a novel two-stage hybrid solution methodology is proposed. In the first stage, products are processed on the serial machines of multiple manufacturers located in two industrial parks. A fuzzy multi-objective scheduling optimization is performed using a modified non-dominated sorting genetic algorithm II (NSGA-II). The result obtained in the first stage is used in the second stage to optimize the distribution scheduling problem using a modified genetic annealing algorithm (GAA). Finally, simulation results verify both the feasibility and efficiency of the proposed solution methodology.
Subject(s)
Algorithms , Commerce , Manufacturing Industry , Empirical Research , Fuzzy Logic , Models, Economic , Models, GeneticABSTRACT
In this paper, the spatial construction models of populations M. persicae and its predatory natural enemy E. graminicola during different periods were simulated by geostatistics, and their spatial relationships were analyzed. The spatial structure of M. persicae population was described by spherical model, showing an aggregated spatial arrangement. Its spatial dependence was 2.0252-4.1495 m, heterogeneity degree was 10,281.36-300,216.30, and sample variance was 12,176.81-303,433.70. The spatial structure of E . graminicola population was also simulated by spherical model, showing an aggregated spatial arrangement. Its spatial dependence was 3.7328-4.8983 m, heterogeneity degree was 1.4482-4.4134, and sample variance was 1.6941-5.8167. The results and methods could be applied to monitor the temporal and spatial dynamics of target insect pest population in tobacco field, and provide scientific basis for ecological control.
