Robust optimization over time (ROOT) is a relatively recent topic in the field of dynamic evolutionary optimization (EDO). The goal of ROOT problems is to find the optimal solution for several environments at the same time. Although significant contributions to ROOT have been published in the past, it is not clear to what extent progress has been made in terms of the type of problem addressed. In particular, we believe that there is confusion regarding what it actually means to solve a ROOT problem. To overcome these limitations, the objective of this paper is twofold. On the one hand, to provide a characterization framework of ROOT problems in terms of their most relevant features, and on the other hand, to organize existing contributions ...
Robust optimization over time is a new approach to solving dynamic optimization problems. It aims to...
Du W, Song W, Tang Y, Jin Y, Qian F. Searching for Robustness Intervals in Evolutionary Robust Optim...
Yazdani D, Cheng R, Yazdani D, Branke J, Jin Y, Yao X. A Survey of Evolutionary Continuous Dynamic O...
Yu X, Jin Y, Tang K, Yao X. Robust optimization over time — A new perspective on dynamic ...
Dynamic optimization problems (DOPs) are those whose specifications change over time during the opti...
The focus of most research in evolutionary dynamic optimization has been tracking moving optimum (TM...
Dynamic optimization problems (DOPs) are those whose specifications change over time, resulting in c...
Robust Optimization Over Time (ROOT) is a new method of solving Dynamic Optimization Problems in res...
Robust optimization over time is a new way to tackle dynamic optimization problems where the goal is...
Many real world problems can be formalized as optimisation problems. Yet, the environment in the rea...
Dynamic optimization problems (DOPs) are problems that change over time. However, most investigation...
Optimization in dynamic environments is a challenging but important task since many real-world optim...
Optimization in dynamic environments is a challenging but important task since many real-world optim...
In dynamic multiobjective optimization problems, the environmental parameters change over time, whic...
In real-world applications, it is often desired that a solution is not only of high performance, but...
Robust optimization over time is a new approach to solving dynamic optimization problems. It aims to...
Du W, Song W, Tang Y, Jin Y, Qian F. Searching for Robustness Intervals in Evolutionary Robust Optim...
Yazdani D, Cheng R, Yazdani D, Branke J, Jin Y, Yao X. A Survey of Evolutionary Continuous Dynamic O...
Yu X, Jin Y, Tang K, Yao X. Robust optimization over time — A new perspective on dynamic ...
Dynamic optimization problems (DOPs) are those whose specifications change over time during the opti...
The focus of most research in evolutionary dynamic optimization has been tracking moving optimum (TM...
Dynamic optimization problems (DOPs) are those whose specifications change over time, resulting in c...
Robust Optimization Over Time (ROOT) is a new method of solving Dynamic Optimization Problems in res...
Robust optimization over time is a new way to tackle dynamic optimization problems where the goal is...
Many real world problems can be formalized as optimisation problems. Yet, the environment in the rea...
Dynamic optimization problems (DOPs) are problems that change over time. However, most investigation...
Optimization in dynamic environments is a challenging but important task since many real-world optim...
Optimization in dynamic environments is a challenging but important task since many real-world optim...
In dynamic multiobjective optimization problems, the environmental parameters change over time, whic...
In real-world applications, it is often desired that a solution is not only of high performance, but...
Robust optimization over time is a new approach to solving dynamic optimization problems. It aims to...
Du W, Song W, Tang Y, Jin Y, Qian F. Searching for Robustness Intervals in Evolutionary Robust Optim...
Yazdani D, Cheng R, Yazdani D, Branke J, Jin Y, Yao X. A Survey of Evolutionary Continuous Dynamic O...