A5027802981- Scheduling and Optimization Algorithms
- Advanced Manufacturing and Logistics Optimization
- Assembly Line Balancing Optimization
- Cloud Computing and Resource Management
- Vehicle Routing Optimization Methods
- Optimization and Search Problems
- Optimization and Packing Problems
- Distributed and Parallel Computing Systems
- IoT and Edge/Fog Computing
- Advanced Control Systems Optimization
- Metaheuristic Optimization Algorithms Research
- Transportation Planning and Optimization
- Maritime Ports and Logistics
- Resource-Constrained Project Scheduling
- Facility Location and Emergency Management
- Business, Education, Mathematics Research
- Business, Innovation, and Economy
- Manufacturing Process and Optimization
- Smart Parking Systems Research
- Supply Chain and Inventory Management
- Transportation and Mobility Innovations
- Advanced Queuing Theory Analysis
- Data Management and Algorithms
- Advanced Multi-Objective Optimization Algorithms
- Urban and Freight Transport Logistics
Universitat Politècnica de València
2015-2024
Universidad Bolivariana del Ecuador
2024
Centro Tecnológico de Investigación, Desarrollo e Innovación en tecnologías de la Información y las Comunicaciones (TIC)
2014-2023
Universidad Continental
2022
Asociación de Investigación Metalúrgica del Noroeste
2022
Zhejiang University
2021
Southeast University
2016-2019
National Taiwan University of Science and Technology
2015
National University of Defense Technology
2015
The University of Tokyo
2015
Taking inspiration from natural behaviors to devise new optimization algorithms has played an important role in the history of field metaheuristics (Sörensen et al. 2017).Unfortunately, last two decades we have been witnessing a trend by which dozens metaphor-based based on most diverse possible set natural, artificial, social, and sometimes even supernatural phenomena are proposed, without clear motivation beyond desire their authors publish papers.
Abstract Nowadays, improving the management of complex supply chains is a key to become competitive in twenty-first century global market. Supply are composed multi-plant facilities that must be coordinated and synchronised cut waste lead times. This paper proposes Distributed Assembly Permutation Flowshop Scheduling Problem (DAPFSP) with two stages model study chains. problem generalisation (DPFSP). The first stage DAPFSP f identical production factories. Each one flowshop produces jobs...