Utilizing hybrid metaheuristic approach to design an agricultural closed-loop supply chain network

Rajabi-Kafshgar, Atefeh; Gholian-Jouybari, Fatemeh; Seyedi, Iman; Hajiaghaei–Keshteli, Mostafa

doi:10.1016/j.eswa.2023.119504

Cited by 44 publications

(6 citation statements)

References 130 publications

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“…Indeed, the objective of avoiding premature convergence and stagnation states can be achieved by selection, replacement, or diversity operators, which ensure the diversity of solutions in the search population or memory [74]. Furthermore, the alternation of the intensification and diversification phases enables profitable exploitation of solutions considered to be the best, as well as the exploration of new search regions [75]. The alternation between the two phases is very useful, as the first guarantees improved solution quality through local search, crossover, or hill climbing, while the second is responsible for generating new solutions due to mutation, perturbation, or restart phenomena [72].…”

Section: Drawbacks and Gaps In The Literaturementioning

confidence: 99%

An Accurate Metaheuristic Mountain Gazelle Optimizer for Parameter Estimation of Single- and Double-Diode Photovoltaic Cell Models

Abbassi,

Saidi,

Urooj

et al. 2023

Mathematics

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Accurate parameter estimation is crucial and challenging for the design and modeling of PV cells/modules. However, the high degree of non-linearity of the typical I–V characteristic further complicates this task. Consequently, significant research interest has been generated in recent years. Currently, this trend has been marked by a noteworthy acceleration, mainly due to the rise of swarm intelligence and the rapid progress of computer technology. This paper proposes a developed Mountain Gazelle Optimizer (MGO) to generate the best values of the unknown parameters of PV generation units. The MGO mimics the social life and hierarchy of mountain gazelles in the wild. The MGO was compared with well-recognized recent algorithms, which were the Grey Wolf Optimizer (GWO), the Squirrel Search Algorithm (SSA), the Differential Evolution (DE) algorithm, the Bat–Artificial Bee Colony Optimizer (BABCO), the Bat Algorithm (BA), Multiswarm Spiral Leader Particle Swarm Optimization (M-SLPSO), the Guaranteed Convergence Particle Swarm Optimization algorithm (GCPSO), Triple-Phase Teaching–Learning-Based Optimization (TPTLBO), the Criss-Cross-based Nelder–Mead simplex Gradient-Based Optimizer (CCNMGBO), the quasi-Opposition-Based Learning Whale Optimization Algorithm (OBLWOA), and the Fractional Chaotic Ensemble Particle Swarm Optimizer (FC-EPSO). The experimental findings and statistical studies proved that the MGO outperformed the competing techniques in identifying the parameters of the Single-Diode Model (SDM) and the Double-Diode Model (DDM) PV models of Photowatt-PWP201 (polycrystalline) and STM6-40/36 (monocrystalline). The RMSEs of the MGO on the SDM and the DDM of Photowatt-PWP201 and STM6-40/36 were 2.042717 ×10−3, 1.387641 ×10−3, 1.719946 ×10−3, and 1.686104 ×10−3, respectively. Overall, the identified results highlighted that the MGO-based approach featured a fast processing time and steady convergence while retaining a high level of accuracy in the achieved solution.

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Section: Drawbacks and Gaps In The Literaturementioning

confidence: 99%

An Accurate Metaheuristic Mountain Gazelle Optimizer for Parameter Estimation of Single- and Double-Diode Photovoltaic Cell Models

Abbassi,

Saidi,

Urooj

et al. 2023

Mathematics

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“…They applied an artificial IoT to increase the security and performance of the network and create a traceable environment. A MILP model to optimize a CLSC in the agricultural industry to minimize strategic and operational costs was developed by Rajabi-Kafshgar et al (2023). They used meta-heuristic algorithms to solve their presented problem.…”

Section: Literature Reviewmentioning

confidence: 99%

A sustainable circular supply chain network design model for electric vehicle battery production using internet of things and big data

et al. 2023

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Designing and developing sustainable circular supply chain networks for electric vehicle (EV) lithium‐ion battery recycling and production requires complex environmental sustainability and economic viability assessment. EVs use a lot of data for battery management and delivering optimum performance, and the Internet of Things (IoT) plays a major role in managing this data. This study develops a bi‐objective mixed‐integer linear programming model for designing a sustainable circular supply chain to manage the manufacturing, remanufacturing, and distribution of EV lithium‐ion batteries under uncertainty using the IoT and big data. The proposed model simultaneously minimizes total costs and CO2 emissions and uses IoT to improve network performance and create a traceable and secure environment. A fuzzy multi‐objective method solves the bi‐objective optimization model under uncertainty, and a simulation algorithm examines the effectiveness of the proposed model through simulated problems.

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“…As mentioned above, the population in MOKA divided into three sub-populations, including 𝑁 1 , 𝑁 2 , and 𝑁 3 . The hybridized strategy is targeted to enrich the exploitation phase in which 𝑁 3 (the worst solution) is generated by SA (Rajabi-Kafshgar et al, 2023). The acceptance or rejection of solutions is determined by applying Metropolis criteria.…”

Section: Hybrid Multi-objective Keshtel Algorithm and Simulating Anne...mentioning

confidence: 99%

An allocation-routing optimization model for integrated solid waste management

Hashemi-Amiri¹,

Mohammadi²,

Rahmanifar³

et al. 2023

Expert Systems with Applications

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Utilizing hybrid metaheuristic approach to design an agricultural closed-loop supply chain network

Cited by 44 publications

References 130 publications

An Accurate Metaheuristic Mountain Gazelle Optimizer for Parameter Estimation of Single- and Double-Diode Photovoltaic Cell Models

An Accurate Metaheuristic Mountain Gazelle Optimizer for Parameter Estimation of Single- and Double-Diode Photovoltaic Cell Models

A sustainable circular supply chain network design model for electric vehicle battery production using internet of things and big data

An allocation-routing optimization model for integrated solid waste management

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