ISA: a hybridization between iterated local search and simulated annealing for multiple-runway aircraft landing problem

Hammouri, Abdelaziz I.; Braik, Malik; Al-Betar, Mohammed Azmi; Awadallah, Mohammed A.

doi:10.1007/s00521-019-04659-y

Cited by 23 publications

(13 citation statements)

References 40 publications

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“…If the CPS restrictions are not considered in the RSP however, then exact methods do not solve large instances in reasonable computation times. The scatter search of [79], the hybrid metaheuristic VND+SA of [51], the hybrid iterated local search / simulated annealing of [58], and the hybrid iterated local search / VND of [69] appear to be good candidate approaches to solve the RSP with one or multiple runways, and with the more general objective of minimizing deviations from target times. They provide good-quality solutions in terms of the gap to the best-known solutions, within reasonable computation times on the OR-library test problems.…”

Section: Discussionmentioning

confidence: 99%

“…In the literature prior to 2010, Genetic Algorithms (GA) were the mostlyused metaheuristic [52,53,54,55,56]). Recently, Tabu Search (TS) and Simulated Annealing (SA) gained much more attention, and became the mostused metaheuristics [10,19,42,51,57,58,59]. Other metaheuristics are also used in the literature, such as Ant Colony Optimization (ACO) [60,61,62], and Variable Neighborhood Descent (VND) [51,63].…”

Section: Stochastic Solution Approachesmentioning

confidence: 99%

“…Recently, Hammouri et al [58] proposed a hybrid method that uses simulated annealing and iterated local search to tackle the ALP, involving one or multiple runways, and taking into consideration time-window restrictions and safety separation constraints. The proposed approach contains two main loops.…”

Section: Simulated Annealingmentioning

confidence: 99%

See 2 more Smart Citations

The aircraft runway scheduling problem: A survey

Ikli

Mancel

Mongeau

et al. 2021

Computers & Operations Research

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The aircraft scheduling problem consists in sequencing aircraft on airport runways and in scheduling their times of operations taking into consideration several operational constraints. It is known to be an NP-hard problem, an ongoing challenge for both researchers and air traffic controllers.The aim of this paper is to present a focused review on the most relevant techniques in the recent literature (since 2010) on the aircraft runway scheduling problem, including exact approaches such as mixed-integer programming and dynamic programming, metaheuristics, and novel approaches based on reinforcement learning. Since the benchmark instances used in the literature are easily solved by high-performance computers and current versions of solvers, we propose a new data set with challenging realistic problems constructed from real-world air traffic.

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Section: Discussionmentioning

confidence: 99%

Section: Stochastic Solution Approachesmentioning

confidence: 99%

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The aircraft runway scheduling problem: A survey

Ikli

Mancel

Mongeau

et al. 2021

Computers & Operations Research

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“…These methods are very effective in generating new legal circuit configurations. Due to large perturbations in the early stages of SA manages the local search procedure [36], the use of matrix group encoding method can generate large perturbations to explore new areas of the search space. By choosing the solution with the highest fitness among the newly generated solutions (i.e., X 1 , X 2 , X 3 ) as the new solution X , the search efficiency can be further improved.…”

Section: ) Inner Loopmentioning

confidence: 99%

Hardware Evolution Based on Improved Simulated Annealing Algorithm in Cyclone V FPSoCs

et al. 2020

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Evolvable hardware (EHW) is an emerging area of research that uses evolutionary algorithms (EAs) to construct circuits without manual intervention. However, this technique confronts two major issues: the evolution efficiency of structures and the computational efficiency of EAs. To address these issues, we construct a novel virtual reconfigurable circuit (VRC) based on artificial neural network (ANN) architecture and develop a promising EA based on improved simulated annealing (ISA) for the research of EHW. Here, ISA escapes the local optimization through an inner loop and expands new search space through an outer loop. Furthermore, several strategies are proposed for the representation, perturbation and selection of solutions (individuals) to reduce the computational burden throughout the entire evolution process. The use of an Intel Cyclone V field programmable system-on-chip (FPSoC) further accelerates the execution of the algorithm and provides designers with much more high-level processing power than that provided by soft-cores. The obtained results show that the proposed method achieves high-speed processing and improves computational efficiency. The results also show that the method has good flexibility and scalability. INDEX TERMS Evolvable hardware, artificial neural networks, improved simulated annealing, algorithm design and analysis, FPSoC.

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“…In land use optimization, there are many mature nonlinear optimization algorithms, such as the simulated annealing algorithm (Hammouri, Braik, Al‐Betar, & Awadallah, 2020), the genetic algorithm (Tian, Li, Han, Liu, & Mo, 2020), and the particle swarm optimization algorithm (Mirghaed, Mohammadzadeh, Salmanmahiny, & Mirkarimi, 2020). However, these models require configuring the land use type for each grid unit in sequence during optimization and performing many iterations, which is not conducive to achieving a significant reduction in optimization time.…”

Section: Introductionmentioning

confidence: 99%

A high‐efficiency global model of optimization design of impervious surfaces for alleviating urban waterlogging in urban renewal

Zhao

et al. 2021

Transactions in GIS

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The rapid expansion and unreasonable design of impervious surfaces caused by urbanization have seriously aggravated urban waterlogging. Determining how to optimize the spatial layout of impervious surfaces is the focus of urban waterlogging prevention in urban renewal. The existing urban‐renewal methods include constructing low‐impact development measures by reducing the area of impervious surfaces or implementing a local high‐strength design based on the ant colony algorithm (ACA) from the viewpoint of optimization design. However, these methods have obvious shortcomings in terms of time efficiency, and their optimized design schemes are insufficient at considering the global impervious surface design. Therefore, to address these problems, the study proposes a coupled model of multivariate linear programming and Soil Conservation Service curve number. The model is employed in the central city of Guangzhou, China. The results show, first, that the optimal design of impervious surfaces in urban renewal is to construct a discontinuous connection of high‐low‐high‐density impervious surfaces; second, that, compared with ACA, our method has higher robustness, increases the average optimization rate by 4.48 to 14.00%, and reduces the optimization time over 30 days to 20.8 s; and third, that the optimal results realize the global low‐strength transformation as complements of the existing design scheme of local high‐strength transformation. This study optimizes methods for alleviating urban waterlogging urban renewal at different scales or intensities.

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ISA: a hybridization between iterated local search and simulated annealing for multiple-runway aircraft landing problem

Cited by 23 publications

References 40 publications

The aircraft runway scheduling problem: A survey

The aircraft runway scheduling problem: A survey

Hardware Evolution Based on Improved Simulated Annealing Algorithm in Cyclone V FPSoCs

A high‐efficiency global model of optimization design of impervious surfaces for alleviating urban waterlogging in urban renewal

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