Combinatorial optimisation for knapsack problems addresses the challenge of selecting discrete items to maximise value under capacity constraints. Such problems are central to resource allocation, ...

In experiments, researchers showed that the disease-spreading insects couldn’t resist the sweet smell of a fungus that infected and killed them. By Jason P. Dinh Watch your back, DEET. There’s a new ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

Researchers have successfully used a quantum algorithm to solve a complex century-old mathematical problem long considered impossible for even the most powerful conventional supercomputers. The ...

ABSTRACT: Supply chain networks, which integrate nodes such as suppliers, manufacturers, and retailers to achieve efficient coordination and allocation of resources, serve as a critical component in ...

Abstract: This study analyses and compares the performance of six heuristic algorithms: Genetic Algorithm (GA), Simulated Annealing (SA), Hybrid (SA+GA), Tabu Search (TS), Ant Colony Optimization (ACO ...

The original version of this story appeared in Quanta Magazine. For computer scientists, solving problems is a bit like mountaineering. First they must choose a problem to solve—akin to identifying a ...

A Python implementation of a branch-and-bound approach (plus a simple greedy heuristic) to solve a variation of the multiple knapsack problem where items have both individual and pairwise benefits.