Swarm Intelligence for Operations and Supply Chain Management
A special issue of Algorithms (ISSN 1999-4893).
Deadline for manuscript submissions: closed (30 September 2019) | Viewed by 900
Special Issue Editor
Interests: supply chain management; multiple criteria decision making; transportation; green logistics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue of Algorithms focuses on recent developments of swarm optimization and its many applications in operations and supply chain management. Swarm intelligence is an important research area of artificial intelligence and operations research that provides adaptive computational tools to solve complex optimization and decision problems. Swarm intelligence and evolutionary computation showed, during the last few decades, a high flexibility in terms of handling variables, constraints, and multiple conflicting objectives. This Special Issue serves as a forum for the development of advanced swarm intelligent algorithms and/or applying existing ones for solving operations management and decision problems. A special interest will be oriented towards non-conventional problems, such as game optimization, dynamic optimization, multi-level and multi-objective optimization.
Researchers are invited to submit their original and unpublished works on the following (but not limited to) areas:
Particle swarm optimization for supply chain management;
Swarm intelligence in games;
Evolutionary artificial bees and fireflies algorithms;
Multi-objective evolutionary algorithm and its applications in operations;
swarm intelligence for multi-level programming and its applications in supply chain management;
Evolutionary computation based machine learning system and its applications; Evolutionary computation based data mining system and its applications; Evolutionary computation in transportation systems, etc.
Prof. Dr. Fouad Ben Abdelaziz
Guest Editor
Manuscript Submission Information
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Keywords
- Swarm Optimization
- Supply Chain Management
- Evolutionary Algorithms
- Metaheuristics
- Quantum Optimization
- Multi-Objective Optimization
- Multi-Level Optimization
- Operations
- Transportation Systems
- Scheduling
- Machine learning Systems
- Evolutionary Computation for Data Mining
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