activity
20192021
most citedEvolutionary Bi-objective Optimization for the Dynamic Chance-Constrained Knapsack Problem Based on Tail Bound Objectives

9 citations · 11 across the 4 of their papers we have counts for

collaborators

5 papers

cs.NE2021

Run-of-Mine Stockyard Recovery Scheduling and Optimisation for Multiple Reclaimers

Hirad Assimi, Ben Koch, Chris Garcia +2

Stockpiles are essential in the mining value chain, assisting in maximising value and production. Quality control of taken minerals from the stockpiles is a major concern for stock…

cs.NE2021

Novelty-Driven Binary Particle Swarm Optimisation for Truss Optimisation Problems

Hirad Assimi, Frank Neumann, Markus Wagner +1

Topology optimisation of trusses can be formulated as a combinatorial and multi-modal problem in which locating distinct optimal designs allows practitioners to choose the best des…

cs.NE2020★ 2 cited

Specific Single- and Multi-Objective Evolutionary Algorithms for the Chance-Constrained Knapsack Problem

Yue Xie, Aneta Neumann, Frank Neumann

The chance-constrained knapsack problem is a variant of the classical knapsack problem where each item has a weight distribution instead of a deterministic weight. The objective is…

cs.NE2020★ 9 cited

Evolutionary Bi-objective Optimization for the Dynamic Chance-Constrained Knapsack Problem Based on Tail Bound Objectives

Hirad Assimi, Oscar Harper, Yue Xie +2

Real-world combinatorial optimization problems are often stochastic and dynamic. Therefore, it is essential to make optimal and reliable decisions with a holistic approach. In this…

cs.NE2019

Evolutionary Algorithms for the Chance-Constrained Knapsack Problem

Yue Xie, Oscar Harper, Hirad Assimi +2

Evolutionary algorithms have been applied to a wide range of stochastic problems. Motivated by real-world problems where constraint violations have disruptive effects, this paper c…