After the seminal books by Martello and Toth (1990) and Kellerer, Pferschy, and Pisinger
(2004), knapsack problems became a classical and rich research area in combinatorial …

Federated learning (FL) is a promising new technology that allows machine learning (ML)
models to be trained locally on edge devices while preserving the privacy of the devices' …

Recent advances in quantum computers are demonstrating the ability to solve problems at a
scale beyond brute force classical simulation. As such, a widespread interest in quantum …

A key issue for moth search algorithm (MS) is the ability to maintain sufficient diversity in the
population so as to be able to track a dynamically changing landscape. However, for the …

The Knapsack Problems (KPs) are classical NP-hard problems in Operations Research
having a number of engineering applications. Several traditional as well as population …

Within state-of-the-art solvers such as IBM-CPLEX, the ability to solve both convex and
nonconvex Mixed-Integer Quadratic Programming (MIQP) problems to proven optimality …

Abstract Grey Wolf Optimizer (GWO) is a new meta-heuristic that mimics the leadership
hierarchy and group hunting mechanism of grey wolves in nature. A binary version is …

In this paper we propose a new hybrid heuristic approach that combines the Quantum
Particle Swarm Optimization technique with a local search method to solve the …

This paper presents an improved fruit fly optimization algorithm (IFFOA) for solving the
multidimensional knapsack problem (MKP). In IFFOA, the parallel search is employed to …

We develop a model of multiwinner elections that combines performance-based measures
of the quality of the committee (such as, eg, Borda scores of the committee members) with …