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Complex System Modeling and Simulation is a peer-reviewed journal published by IEEE, covering Scheduling and Optimization Algorithms, Advanced Manufacturing and Logistics Optimization, Metaheuristic Optimization Algorithms Research.
| Publisher | IEEE |
|---|---|
| Reference style | Numbered (IEEE) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, and C. Lee, "A representative article title," Complex System Modeling and Simulation, vol. 12, no. 3, pp. 45–58, 2023.
Formats any DOI in Complex System Modeling and Simulation style. No sign-up. |
| Publishes research in | Scheduling and Optimization Algorithms Advanced Manufacturing and Logistics Optimization Metaheuristic Optimization Algorithms Research Advanced Multi-Objective Optimization Algorithms Vehicle Routing Optimization Methods |
| ISSN | 2096-9929 |
| Citation impact (2-yr) | 2.35 |
| h-index | 23 |
| i10-index | 56 |
| Total citations | 2,071 |
| Open access | Yes |
| Top institutions publishing here | Liaocheng University |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
As the critical component of manufacturing systems, production scheduling aims to optimize objectives in terms of profit, efficiency, and energy consumption by reasonably determining the main factors including processing path, machine assignment, execute time and so on. Due to the large scale and strongly coupled constraints nature, as well as the real-time solving requirement in…
To meet the multi-cooperation production demand of enterprises, the distributed permutation flow shop scheduling problem (DPFSP) has become the frontier research in the field of manufacturing systems. In this paper, we investigate the DPFSP by minimizing a makespan criterion under the constraint of sequence-dependent setup times. To solve DPFSPs, significant developments of some metaheuristic algorithms…
A hyper-heuristic algorithm is a general solution framework that adaptively selects the optimizer to address complex problems. A classical hyper-heuristic framework consists of two levels, including the high-level heuristic and a set of low-level heuristics. The low-level heuristics to be used in the optimization process are chosen by the high-level tactics in the hyper-heuristic. In…
Nonlinear Equations (NEs), which may usually have multiple roots, are ubiquitous in diverse fields. One of the main purposes of solving NEs is to locate as many roots as possible simultaneously in a single run, however, it is a difficult and challenging task in numerical computation. In recent years, Intelligent Optimization Algorithms (IOAs) have shown…
Dynamic task allocation of unmanned aerial vehicle swarms for ground targets is an important part of unmanned aerial vehicle (UAV) swarms task planning and the key technology to improve autonomy. The realization of dynamic task allocation in UAV swarms for ground targets is very difficult because of the large uncertainty of swarms, the target and…
