An extension of the non-inferior set estimation algorithm for many objectives

Raimundo, Marcos M.; Ferreira, Paulo Augusto Valente; Zuben, Fernando J. Von

doi:10.1016/j.ejor.2019.11.017

Cited by 11 publications

(3 citation statements)

References 40 publications

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“…The supported efficient paths can be identified using solution approaches such as the weighting method, NISE, and MONISE (Cohon et al Fig. 5 Network utilization and worst-case set arcs selected for alteration considering only the least-cost path between each od pair and given t = 35 in Periods: a t = 0 , b t = 1 , c t = 2 , d t = 3 , e t = 4, f t = 5 , g t = 6 , h t = 7 , i t = 8 and j t = 9 1979; Balachandran and Gero 1985;Medrano and Church 2014;Raimundo et al 2020). Whereas supported efficient paths are typically sought as they can be readily identified using traditional linear optimization approaches, research has found that in some instances, unsupported efficient paths can constitute a large proportion of the efficient solutions (Matisziw et al 2020).…”

Section: Discussionmentioning

confidence: 99%

Contextualizing vulnerability of ecological systems to landscape alteration

2023

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Context A variety of processes, such as urbanization and development projects, can degrade connectivity in habitat systems, presenting significant threats to species persistence. Effective mitigation of such threats depends in part on knowledge about where and when landscape changes may occur as well as how species may respond to changes in the landscape. Objectives A spatial decision support framework for informing planning efforts involving alterations to the landscape that may impact prospects for species’ inter-habitat connectivity is proposed. Methods As a variety of movement objectives are thought to influence species’ perception of habitat connectivity, efficient paths supporting movement among habitats in a planning period are identified by way of a multiobjective least-cost path model. This set of paths represent the best options for inter-habitat connectivity in a particular planning period. Provided this representation of inter-habitat connectivity, the worst-case scenario of landscape alteration on inter-habitat connectivity is then identified. This multi-level optimization process is repeated over a set of planning periods until inter-habitat connectivity has been completely eliminated. Results The results indicate that representing habitat connectivity with a limited set of paths reflecting a single objective for species movement could result in an overestimate of a habitat system’s resilience to landscape change over time. Representations of connectivity involving a more diverse set of paths reflecting tradeoffs among a set of objectives offer more robust representation of complex biological movements. Conclusions The application results indicate that landscape alterations occurring more proximate to habitat patches have the highest negative impact to connectivity. In addition, whereas alterations to the landscape may have no or little impact on inter-habitat connectivity in one planning period, when coupled with future alterations they can result in significant barriers to connectivity.

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Section: Discussionmentioning

confidence: 99%

Contextualizing vulnerability of ecological systems to landscape alteration

2023

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“…When PSO is performed, non-inferior solutions will be generated in a single cycle, and the external files responsible for storing non-inferior solutions will also interfere with the operation efficiency of PSO. The external file is truncated, and the impact of the external file storing the noninferior solution on the algorithm is controlled by setting the upper and lower limits of the file size [15].…”

Section: Figure 5: the Flow Chart Of Optimization Of Forging And Form...mentioning

confidence: 99%

Parameter Optimization of the Forging and Forming Process Using Particle Swarm Optimization

2022

IJOMAM

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To find the best process parameters when forging blanks and improve the imperfections of the traditional numerical simulation method, particle swarm optimization (PSO) with excellent problem optimization ability will be used to optimize the parameters. From the perspective of the material itself and the energy saving of forging and forming, the most suitable parameter results can be found using this algorithm. The modeling and simulation of aluminum forging is carried out. The simulation software is used to summarize the action laws of the initial temperature of 440 °C, 460 °C, 500 °C and the forging speed of 3mm/s to 5mm/s. The simulation results are recorded and the standard deviation of the outlet surface temperature is calculated, which are used as the experimental data to establish a support vector machine (SVM) model for further fitting and calculation of the data. Then a multi-objective optimization model is established with the initial temperature and forging speed as variables and the goal of reducing the standard deviation of temperature and energy consumption. PSO is used to further solve the model to find the optimal combination of process parameters to reduce energy consumption and ensure material quality, to achieve the purpose of parameter optimization of forging and forming process. The results show that when the initial temperature is 450 °C and the forging speed is 4.4 mm/s, the material quality can be effectively improved while reducing energy consumption. Compared with the original scheme, the new scheme achieves the purpose of optimizing parameters. It has a great reference for the selection of parameter optimization of the forging and forming process and the application of PSO in the optimization process.

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“…In the case that more than two objectives are to be considered, the NISE approach becomes more complicated [ 35 , 36 ]. In order to cope with these complexities, multiple objective non-inferior set estimation (MONISE) techniques have been proposed to extend the NISE concept to characterize the supported efficient frontier when more than two criteria are involved [ 37 – 39 ].…”

Section: Introductionmentioning

confidence: 99%

Modeling habitat connectivity in support of multiobjective species movement: An application to amphibian habitat systems

2020

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Reasoning about the factors underlying habitat connectivity and the inter-habitat movement of species is essential to many areas of biological inquiry. In order to better describe and understand the ways in which the landscape may support species movement, an increasing amount of research has focused on identification of paths or corridors that may be important in providing connectivity among habitat. The least-cost path problem has proven to be an instrumental analytical tool in this sense. A complicating aspect of such path identification methods is how to best reconcile and integrate the array of criteria or objectives that species may consider in traversal of a landscape. In cases where habitat connectivity is thought to be influenced or guided by multiple objectives, numerous solutions to least-cost path problems can exist, representing tradeoffs between the objectives. In practice though, identification of these solutions can be very challenging and as such, only a small proportion of them are typically examined leading to a weak characterization of habitat connectivity. To address this computational challenge, a multiobjective optimization framework is proposed. A generalizable multiobjective least-cost path model is first detailed. A non-inferior set estimation (MONISE) algorithm for identifying supported efficient solutions to the multiobjective least-cost path model is then described. However, it is well known that unsupported efficient solutions (which are equally important) can also exist, but are typically ignored given that they are more difficult to identify. Thus, to enable the identification of the full set of efficient solutions (supported and unsupported) to the multiobjective model, a multi-criteria labeling algorithm is then proposed. The developed framework is applied to assess different conceptualizations of habitat connectivity supporting amphibian movement in a wetland system. The results highlight the range of tradeoffs in characterizations of connectivity that can exist when multiple objectives are thought to contribute to movement decisions and that the number of unsupported efficient solutions (which are typically ignored) can vastly outweigh that of the supported efficient solutions.

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An extension of the non-inferior set estimation algorithm for many objectives

Cited by 11 publications

References 40 publications

Contextualizing vulnerability of ecological systems to landscape alteration

Contextualizing vulnerability of ecological systems to landscape alteration

Parameter Optimization of the Forging and Forming Process Using Particle Swarm Optimization

Modeling habitat connectivity in support of multiobjective species movement: An application to amphibian habitat systems

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