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 …

Semiconductor final testing scheduling problem (SFTSP) has extensively been studied in
advanced manufacturing and intelligent scheduling fields. This paper presents a Q-learning …

Hyper-heuristic is a class of methodologies which automates the process of selecting or
generating a set of heuristics to solve various optimization problems. A traditional hyper …

In this paper, we extend a novel model for source-separated waste collection and
transportation, the green location routing problem with multi-compartment (GLRPFMC), for …

Silicon electrodes are widely used in semiconductor etching machines. The periodic
consumption of silicon electrodes has become an important consumable in wafer …

In this work we present a simple state-of-the-art selection hyperheuristic called Fair-Share
Iterated Local Search (FS-ILS). FS-ILS is an iterated local search method using a …

In this work we conduct a comparative study of several publicly available, state-of-the-art
hyper-heuristics for HyFlex in order to assess their generality across domains. To this …

Hyper-heuristics are general-purpose heuristic search methodologies for solving
combinatorial optimization problems (COPs). Research findings have revealed that hyper …

To date, algorithms for real-world problems are most commonly designed following a
manual, adhoc, trial & error approach, making algorithm design a tedious, time-consuming …

The automated design of search techniques is a recent trend in artificial intelligence
research. Unfortunately, the majority of the automated design approaches are developed …