Hyper-heuristics have emerged as a way to raise the level of generality of search techniques
for computational search problems. This is in contrast to many approaches, which represent …

The timetabling problem is common to academic institutions such as schools, colleges or
universities. It is a very hard combinatorial optimisation problem which attracts the interest of …

This paper addresses an extension of the flexible job shop scheduling problem by
considering that jobs need to be moved around the shop-floor by a set of vehicles. Thus, this …

Simulated Annealing (SA) is one of the oldest metaheuristics and has been adapted to solve
many combinatorial optimization problems. Over the years, many authors have proposed …

We propose a survey of the research contributions on the field of Educational Timetabling
with a specific focus on “standard” formulations and the corresponding benchmark …

Breast cancer has become a common malignancy in women. However, early detection and
identification of this disease can save many lives. As computer-aided detection helps …

Long-chain polyunsaturated fatty acids (LC-PUFAs), particularly the omega-3 LC-PUFAs
eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), and docosahexaenoic acid …

The workflow scheduling in the cloud computing environment is a well-known NP-complete
problem, and metaheuristic algorithms are successfully adapted to solve this problem more …

Feature selection (FS) is mainly used as a pre-processing tool to reduce dimensionality by
eliminating irrelevant or redundant features to be used for a machine learning or data mining …

Convolutional neural networks (CNNs) provide the best accuracy for disparity estimation.
However, CNNs are computationally expensive, making them unfavorable for resource …