The resource-constrained project scheduling problem is to schedule activities subject to
precedence and resource constraints such that the makespan is minimized. It has become a …

The application of artificial intelligence in everyday life is becoming all-pervasive and
unavoidable. Within that vast field, a special place belongs to biomimetic/bio-inspired …

Job shop scheduling (JSS) is a process of optimizing the use of limited resources to improve
the production efficiency. JSS has a wide range of applications, such as order picking in the …

Task allocation is a crucial issue of mobile crowdsensing. The existing crowdsensing
systems normally select the optimal participants giving no consideration to the sudden …

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

In this paper, a genetic programming hyper heuristic (GP-HH) algorithm is proposed to solve
the distributed assembly permutation flow-shop scheduling problem with sequence …

In recent years, machine learning techniques, especially genetic programming (GP), have
been a powerful approach for automated design of the priority rule-heuristics for the …

Dynamic flexible job shop scheduling (JSS) has received widespread attention from
academia and industry due to its practical application value. It requires complex routing and …

In this paper, an efficient decomposition-based multi-objective genetic programming hyper-
heuristic (MOGP-HH/D) approach is proposed for the multi-skill resource constrained project …

In the real world, there are many complex problems in engineering. Every problem has a
level of computational complexity, starting from simple problems and reaching NP-hard …