Scheduling in Industrial environment toward future: insights from Jean-Marie Proth

M Khakifirooz, M Fathi, A Dolgui… - International Journal of …, 2024 - Taylor & Francis
According to [Dolgui, Alexandre, and Jean Marie Proth. 2010. Supply Chain Engineering:
Useful Methods and Techniques. Vol. 539. Springer.], advancing tactical levels in production …

Survey on genetic programming and machine learning techniques for heuristic design in job shop scheduling

F Zhang, Y Mei, S Nguyen… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
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 …

A data-driven simulation-optimization framework for generating priority dispatching rules in dynamic job shop scheduling with uncertainties

H Wang, T Peng, A Nassehi, R Tang - Journal of Manufacturing Systems, 2023 - Elsevier
Modeling and optimizing dynamic job shop scheduling problems (DJSSP) without ample
assumptions is inherently challenging due to the increasing complexity and uncertainty …

A priority rule for scheduling shared due dates in the resource-constrained project scheduling problem

WR Strahl, CE Gounaris - Computers & Industrial Engineering, 2023 - Elsevier
In resource-constrained project scheduling, project milestones, rental equipment, contracted
labor, and product development checkpoints all conceptually impose shared due dates …

[HTML][HTML] Surrogate model for memetic genetic programming with application to the one machine scheduling problem with time-varying capacity

FJ Gil-Gala, MR Sierra, C Mencía, R Varela - Expert Systems with …, 2023 - Elsevier
Surrogate evaluation is a useful, if not the unique, technique in population-based
evolutionary algorithms where exact fitness calculation is too expensive. This situation …

Automated design of priority rules for resource-constrained project scheduling problem using surrogate-assisted genetic programming

J Luo, M Vanhoucke, J Coelho - Swarm and Evolutionary Computation, 2023 - Elsevier
In the past few years, the genetic programming approach (GP) has been successfully used
by researchers to design priority rules for the resource-constrained project scheduling …

[HTML][HTML] A cooperative coevolutionary genetic programming hyper-heuristic for multi-objective makespan and cost optimization in cloud workflow scheduling

T Zaki, Y Zeiträg, R Neves, JR Figueira - Computers & Operations Research, 2024 - Elsevier
This study presents a novel multi-objective approach for NP-hard workflow scheduling in
cloud computing environments. Traditional rule-based heuristics offer flexibility but lack …

Investigating the best automatic programming method in predicting the aerodynamic characteristics of wind turbine blade

S Arslan, K Koca - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Automatic programming (AP) is a subfield of artificial intelligence (AI) that can automatically
generate computer programs and solve complex engineering problems. This paper presents …

A surrogate-assisted dual-tree genetic programming framework for dynamic resource constrained multi-project scheduling problem

HJ Chen, XY Li, L Gao - International Journal of Production …, 2024 - Taylor & Francis
Genetic programming has achieved great success in project scheduling by generating
Priority Rules (PRs) through evolution. However, the frequent disturbance factors in practice …

Duration and resource constraint prediction models for construction projects using regression machine learning method

G Selvam, M Kamalanandhini… - Engineering …, 2024 - emerald.com
Purpose The construction projects are highly subjected to uncertainties, which result in
overruns in time and cost. Realistic estimates of workforce and duration are imperative for …