The bin packing problem is a well-studied problem in combinatorial optimization. In the
classical bin packing problem, we are given a list of real numbers in (0, 1] and the goal is to …

Invasive species are a major threat to the economy, the environment, health, and thus
human well-being. The international community, including the United Nations' Global …

Recently, training with adversarial examples, which are generated by adding a small but
worst-case perturbation on input examples, has improved the generalization performance of …

Symbolic regression (SR) is the task of learning a model of data in the form of a
mathematical expression. By their nature, SR models have the potential to be accurate and …

In this paper, we propose mathematical optimization models of household energy units to
optimally control the major residential energy loads while preserving the user preferences …

Vehicular crowd sensing systems are designed to achieve large spatio-temporal sensing
coverage with low-cost in deployment and maintenance. For example, taxi platforms can be …

Mobile crowdsensing (MCS) is a popular paradigm to collect sensed data for numerous
sensing applications. With the increment of tasks and workers in MCS, it has become …

Collaborative computation offloading in mobile edge computing where edge users offload
tasks opportunistically to resourceful neighboring mobile devices (MDs), offers a promising …

Remote zero-shot object recognition, which involves offloading the zero-shot recognition
task from one mobile device to a remote mobile edge computing (MEC) server or another …

Bin packing problem (BPP) is a classical combinatorial optimization problem widely used in
a wide range of fields. The main aim of this paper is to propose a new variant of whale …