Flexible Runway Scheduling with non-linear Noise Restrictions using a Tabu Search Algorithm

In response to the growing demand for air travel, major airports are approaching critical thresholds in their infrastructure capacity. As the transportation sector continues to expand, it is increasingly important to address environmental concerns that arise from aspects, such as noise annoyance and fuel consumption. This paper aims to enhance...

AI-Assisted Design & Optimization for Predictive Maintenance: A Case Study using Deep Learning and Search Metaheuristics for Structural Health Monitoring in Aviation

One of the classical solutions to maintain the aircraft structural integrity is to rely on the analysis of non-destructive testing (NDT) inspector with various inspection methods. However, it is relatively expensive in matter of time and costs to train human resources until the certification is reached. Further, in majority of the cases of...

Distribution Network Reconfiguration Considering the Impacts of Local Renewable Generation and External Power Grid

The distribution network (DN) reconfiguration is a well-known optimal power flow (OPF) problem. However, with the transition of DN from 'passive' to 'active', new technical challenges arise in DN reconfiguration. This article addresses two key issues in this regard. Firstly, the integration of local renewable generation (LRG) introduces...

Hybrid differential evolution algorithm for the resource constrained project scheduling problem with a flexible project structure and consumption and production of resources

The resource constrained project scheduling problem with a flexible project structure and consumption and production of resources, involves making a selection of activities and scheduling these activities in order to minimize the makespan, subject to precedence and resource constraints. Since finding a feasible selection of activities is NP...

Modeling Strong Physically Unclonable Functions with Metaheuristics

Evolutionary algorithms have been successfully applied to attack Physically Unclonable Functions (PUFs). CMA-ES is recognized as the most powerful option for a type of attack called the reliability attack. In this paper, we take a step back and systematically evaluate several metaheuristics for the challenge-response pair-based attack on...

Models and heuristics for hard routing and knapsack problems

One of the world’s biggest challenges is that living beings have to share a limited amount of resources. As people of science, we strive to find innovative ways to better use these resources, to reach and positively affect more and more people. In the field of optimization, we aim at finding an optimal allocation of limited sets of resources to...

Salp Swarm Optimization: A critical review

In the crowded environment of bio-inspired population-based metaheuristics, the Salp Swarm Optimization (SSO) algorithm recently appeared and immediately gained a lot of momentum. Inspired by the peculiar spatial arrangement of salp colonies, which are displaced in long chains following a leader, this algorithm seems to provide an interesting...

An efficient metaheuristic to solve the project portfolio selection and scheduling problem for industrial projects

Industrial companies aim for optimizing profit from delivering project outcomes. Maximizing profit relies on optimization of using resources, production capacity and available time. To reach this goal, companies are typically reliant on planning and production schedules. This problem is known as the project portfolio selection and scheduling...

2017 IEEE competition on modern heuristic optimizers for smart grid operation: Testbeds and results

This paper summarizes the two testbeds, datasets, and results of the IEEE PES Working Group on Modern Heuristic Optimization (WGMHO) 2017 Competition on Smart Grid Operation Problems. The competition is organized with the aim of closing the gap between theory and real-world applications of evolutionary computation. Testbed 1 considers...

Meeting Short-Term Production Targets: Controlling Short-Term Deviations from Production Targets by Blending Geological Confidence Classes of Reporting Standards

Meeting short-term production targets is desired by many companies, since this would enable them to fine tune the processing operation, meet budget plans and obey contract requirements. Recently stochastic optimization solutions have been developed requiring geostatistical simulations as input. The significant value added has been demonstrated,...

Optimal scheduling and routing of free-range AGVs at large scale automated container terminals

This work tackles the problem of controlling operations at an automated container terminal. In the context of large supply chains, there is a growing trend for increasing productivity and economic efficiency. New optimization models and algorithms are provided for scheduling and routing equipment that is moving containers in a quay area,...