This article provides a survey on the highly popular metaheuristic framework, the adaptive
large neighborhood search (ALNS). The basic concepts of ALNS are discussed in this …

Parameter tuning, that is, to find appropriate parameter settings (or configurations) of
algorithms so that their performance is optimized, is an important task in the development …

This paper presents a systematic literature review on general parameter control for
evolutionary and swarm-based algorithms. General methods can be applied to any …

Bio-inspired optimization (including Evolutionary Computation and Swarm Intelligence) is a
growing research topic with many competitive bio-inspired algorithms being proposed every …

This paper considers a cooperative system between electric vehicles and drones in last-mile
logistics operations. This form of cooperation is presented as electric vehicle–drone routing …

The home health care routing and scheduling problem (HHCRSP), a challenging
operational problem in the field of home health care (HHC), consists of assigning suitable …

In this paper we propose a hybrid metaheuristic based on Particle Swarm Optimization,
which we tailor on a portfolio selection problem. To motivate and apply our hybrid …

A number of recent studies have adopted long short-term memory (LSTM) in extensive
applications, such as handwriting recognition and time series prediction, with considerable …

Meta-heuristic algorithms should be compared using the best parameter values for all the
involved algorithms. However, this is often unrealised despite the existence of several …

The electric travelling salesman problem with time windows (ETSPTW) is an extension of the
well-known travelling salesman problem with time windows (TSPTW). The ETSPTW …