Improved Adaptive Integer form of Population-Based Incremental Learning and Reactive Tabu Search for an Integrated Energy Supply and Demand Optimization Framework in Factories
Author:
Affiliation:
1. Corporate R&D Headquarters in Mitsubishi Electric Co., Ltd and Meiji University,Kanagawa,Japan
2. Graduate School of Advanced Mathematical Sciences, Meiji University,Tokyo,Japan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10463165/10463194/10463240.pdf?arnumber=10463240
Reference17 articles.
1. Improved Parallel Reactive Hybrid Particle Swarm Optimization using Improved Neighborhood Schedule Generation Method for the Integrated Framework of Optimal Production Scheduling and Operational Planning of an Energy Plant in a Factory
2. Solving the energy-efficient job shop scheduling problem: a multi-objective genetic algorithm with enhanced local search for minimizing the total weighted tardiness and total energy consumption
3. A novel mathematical model and multi-objective method for the low-carbon flexible job shop scheduling problem
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