A simheuristic approach using the NSGA-II to solve a bi-objective stochastic flexible job shop problem

Rodríguez-Espinosa, Camilo Andrés; González-Neira, Eliana María; Zambrano-Rey, Gabriel Mauricio

doi:10.1080/17477778.2023.2231877

Cited by 4 publications

(1 citation statement)

References 76 publications

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“…Similarly, Bayliss and Panadero [30] combined simheuristics with machine learning models to address the facility location and queuing problem in emergency scenarios where a large number of citizens require medical treatment. Simheuristics has also been combined with evolutionary algorithms to solve manufacturing problems [31,32]. Likewise, it has been used to solve stochastic versions of well-known optimization problems [28,33].…”

Section: A Review Of the Simheuristics Concept And Recent Applicationsmentioning

confidence: 99%

Solving NP-Hard Challenges in Logistics and Transportation under General Uncertainty Scenarios Using Fuzzy Simheuristics

Juan,

Rabe,

Ammouriova

et al. 2023

Algorithms

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In the field of logistics and transportation (L&T), this paper reviews the utilization of simheuristic algorithms to address NP-hard optimization problems under stochastic uncertainty. Then, the paper explores an extension of the simheuristics concept by introducing a fuzzy layer to tackle complex optimization problems involving both stochastic and fuzzy uncertainties. The hybrid approach combines simulation, metaheuristics, and fuzzy logic, offering a feasible methodology to solve large-scale NP-hard problems under general uncertainty scenarios. These scenarios are commonly encountered in L&T optimization challenges, such as the vehicle routing problem or the team orienteering problem, among many others. The proposed methodology allows for modeling various problem components—including travel times, service times, customers’ demands, or the duration of electric batteries—as deterministic, stochastic, or fuzzy items. A cross-problem analysis of several computational experiments is conducted to validate the effectiveness of the fuzzy simheuristic methodology. Being a flexible methodology that allows us to tackle NP-hard challenges under general uncertainty scenarios, fuzzy simheuristics can also be applied in fields other than L&T.

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Section: A Review Of the Simheuristics Concept And Recent Applicationsmentioning

confidence: 99%

Solving NP-Hard Challenges in Logistics and Transportation under General Uncertainty Scenarios Using Fuzzy Simheuristics

Juan,

Rabe,

Ammouriova

et al. 2023

Algorithms

View full text Add to dashboard Cite

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A hybrid simheuristic algorithm for solving bi-objective stochastic flexible job shop scheduling problems

Nessari,

Tavakkoli-Moghaddam,

Bakhshi-Khaniki

et al. 2024

Decision Analytics Journal

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Flexible Assembly Job Shop Scheduling Considering Assembly Sequence Variation Under Dual-Resource Constraints Using Discrete Barnacles Mating Optimizer Algorithm

Lu,

Usman

2024

IEEE Access

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A simheuristic approach using the NSGA-II to solve a bi-objective stochastic flexible job shop problem

Cited by 4 publications

References 76 publications

Solving NP-Hard Challenges in Logistics and Transportation under General Uncertainty Scenarios Using Fuzzy Simheuristics

Solving NP-Hard Challenges in Logistics and Transportation under General Uncertainty Scenarios Using Fuzzy Simheuristics

A hybrid simheuristic algorithm for solving bi-objective stochastic flexible job shop scheduling problems

Flexible Assembly Job Shop Scheduling Considering Assembly Sequence Variation Under Dual-Resource Constraints Using Discrete Barnacles Mating Optimizer Algorithm

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