7 papers · 1 filter
Insights from Multi-tasking the EAX Algorithm for the Travelling Salesperson Problem
Liam Wigney, Aneta Neumann, Yew-Soon Ong +1
Evolutionary multitasking allows several related problems to be solved in a single run of an algorithm. In this paper, we investigate integrating evolutionary multitasking with Edg…
Multitask Pareto Optimization for Monotone Submodular Problems with Dynamic Constraints
Liam Wigney, Frank Neumann
Evolutionary multitasking is a recent approach that solves multiple related optimization problems within a single evolutionary run, rather than addressing each problem separately.…
Analysis of Multitasking Pareto Optimization for Monotone Submodular Problems
Liam Wigney, Frank Neumann
Pareto optimization via evolutionary multi-objective algorithms has been shown to efficiently solve constrained monotone submodular functions. Traditionally when solving multiple p…
On the Use of Iterative Problem Solving for the Traveling Salesperson Problem with Changing Time Window Constraints
Hy Nguyen, Thanh Nguyen Pham, Helen Yuliana Angmalisang +2
In many real-world settings, problem instances that need to be solved are quite similar, and knowledge from previous optimization runs can potentially be utilized. We explore this…
Greedy Approaches for Packing While Travelling with Deterministic and Stochastic Constraints
Thilina Pathirage Don, Aneta Neumann, Frank Neumann
The travelling thief problem (TTP) is a well-known multi-component optimisation problem that captures the interdependence between two components: the tour across cities and the pac…
Sliding Window Bi-Objective Evolutionary Algorithms for Optimizing Chance-Constrained Monotone Submodular Functions
Xiankun Yan, Aneta Neumann, Frank Neumann
Variants of the GSEMO algorithm using multi-objective formulations have been successfully analyzed and applied to optimize chance-constrained submodular functions. However, due to…
Archive-based Single-Objective Evolutionary Algorithms for Submodular Optimization
Frank Neumann, Günter Rudolph
Constrained submodular optimization problems play a key role in the area of combinatorial optimization as they capture many NP-hard optimization problems. So far, Pareto optimizati…