優化方法及軟件發表有關優化方法理論和實現的最新進展的參考論文，特別強調軟件開發和算法設計之間的接口。主題包括:線性、非線性、離散、隨機優化和最優控制算法和計算機代碼的理論、實現和性能評估。具體包括二次曲線、半定、混合整數、網絡、非光滑、多目標和確定性或非確定性算法的全局優化。用于互補、變分不等式和平衡問題的算法和軟件，也用于求解反問題、非線性方程組和參數相關算子的數值研究。高效和用戶友好的實現的各個方面:例如自動微分、大規模并行優化、分布式計算、在線算法、錯誤敏感性和有效性分析、問題縮放、停止標準和符號數字接口。具有明顯應用潛力的理論研究，以及在工程、機器學習、數據挖掘、經濟學、金融學、生物學或醫學等領域成功應用經過特別調整的優化方法和軟件。這些提交不應該僅僅包括直接使用標準優化技術。

Topics include: Theory, implementation and performance evaluation of algorithms and computer codes for linear, nonlinear, discrete, stochastic optimization and optimal control. This includes in particular conic, semi-definite, mixed integer, network, non-smooth, multi-objective and global optimization by deterministic or nondeterministic algorithms. Algorithms and software for complementarity, variational inequalities and equilibrium problems, and also for solving inverse problems, systems of nonlinear equations and the numerical study of parameter dependent operators. Various aspects of efficient and user-friendly implementations: e.g. automatic differentiation, massively parallel optimization, distributed computing, on-line algorithms, error sensitivity and validity analysis, problem scaling, stopping criteria and symbolic numeric interfaces. Theoretical studies with clear potential for applications and successful applications of specially adapted optimization methods and software to fields like engineering, machine learning, data mining, economics, finance, biology, or medicine. These submissions should not consist solely of the straightforward use of standard optimization techniques.