JSE Algorithm & Computation Guide
Guides the design, benchmarking, and reporting of optimization and simulation algorithms for the Journal of Systems Engineering.
Designed specifically for researchers targeting 《系统工程学报》 (Journal of Systems Engineering, Tianjin University), this skill guides the formulation, auditing, and documentation of exact, decomposition, heuristic, simulation, and learning-based solution routes. It ensures that algorithmic novelty directly addresses structural problem characteristics rather than relying on generic metaheuristics, enforcing rigorous standards for executable pseudocode, convergence guarantees, fair baseline comparisons, ablation experiments, scalability stress-testing, and reproducible computational environment reporting.
主な機能
01Selects problem-driven solution routes including exact solvers, Benders decomposition, ADMM, and heuristics based on model structure
02Provides standardized reporting checklists for scalability gradients, timeout boundaries, and computing environments
03Constructs fair benchmarking frameworks with unified compute budgets, ablation studies, and meaningful baselines
041,086 GitHub stars
05Generates standardized, executable pseudocode aligned with mathematical model notation and state transitions
06Establishes theoretical convergence, bounds, optimality gaps, and diagnostic residual criteria
ユースケース
01Auditing manuscript algorithm sections to eliminate weak baselines, reproducibility gaps, and rejection risks
02Writing structured computational experiments, ablation tables, and convergence analyses for journal submissions
03Designing decomposition or heuristic algorithms tailored to complex systems engineering problems