5 papers
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…
On the Use of Evolutionary Optimization for the Dynamic Chance Constrained Open-Pit Mine Scheduling Problem
Ishara Hewa Pathiranage, Aneta Neumann
Open-pit mine scheduling is a complex real world optimization problem that involves uncertain economic values and dynamically changing resource capacities. Evolutionary algorithms…
On the Use of Bi-Objective Evolutionary Algorithms for the Stochastic MKP under Dynamic Constraints
Ishara Hewa Pathiranage, Aneta Neumann
The multiple knapsack problem (MKP) generalizes the classical knapsack problem by assigning items to multiple knapsacks subject to capacity constraints. It is used to model many re…
Bi-Objective Evolutionary Optimization for Large-Scale Open Pit Mine Scheduling Problem under Uncertainty with Chance Constraints
Ishara Hewa Pathiranage, Aneta Neumann
The open-pit mine scheduling problem (OPMSP) is a complex, computationally expensive process in long-term mine planning, constrained by operational and geological dependencies. Tra…
Evolutionary Algorithm for Chance Constrained Quadratic Multiple Knapsack Problem
Kokila Kasuni Perera, Aneta Neumann
Quadratic multiple knapsack problem (QMKP) is a combinatorial optimisation problem characterised by multiple weight capacity constraints and a profit function that combines linear…