@article{53205,
  author       = {{Tavana, Madjid and Sorooshian, Shahryar}},
  issn         = {{1568-4946}},
  journal      = {{Applied Soft Computing}},
  keywords     = {{Software}},
  publisher    = {{Elsevier BV}},
  title        = {{{A systematic review of the soft computing methods shaping the future of the metaverse}}},
  doi          = {{10.1016/j.asoc.2023.111098}},
  volume       = {{150}},
  year         = {{2024}},
}

@article{53215,
  author       = {{Tavana, Madjid and Heidary, Mohammad Saeed and Mina, Hassan}},
  issn         = {{1568-4946}},
  journal      = {{Applied Soft Computing}},
  keywords     = {{Software}},
  publisher    = {{Elsevier BV}},
  title        = {{{A fuzzy preference programming and weighted influence non-linear gauge system for mission architecture assessment at NASA}}},
  doi          = {{10.1016/j.asoc.2023.110572}},
  volume       = {{145}},
  year         = {{2023}},
}

@article{48848,
  abstract     = {{We build upon a recently proposed multi-objective view onto performance measurement of single-objective stochastic solvers. The trade-off between the fraction of failed runs and the mean runtime of successful runs \textendash both to be minimized \textendash is directly analyzed based on a study on algorithm selection of inexact state-of-the-art solvers for the famous Traveling Salesperson Problem (TSP). Moreover, we adopt the hypervolume indicator (HV) commonly used in multi-objective optimization for simultaneously assessing both conflicting objectives and investigate relations to commonly used performance indicators, both theoretically and empirically. Next to Penalized Average Runtime (PAR) and Penalized Quantile Runtime (PQR), the HV measure is used as a core concept within the construction of per-instance algorithm selection models offering interesting insights into complementary behavior of inexact TSP solvers. \textbullet The multi-objective perspective is naturally generalizable to multiple objectives. \textbullet Proof of relationship between HV and the PAR in the considered bi-objective space. \textbullet New insights into complementary behavior of stochastic optimization algorithms.}},
  author       = {{Bossek, Jakob and Kerschke, Pascal and Trautmann, Heike}},
  issn         = {{1568-4946}},
  journal      = {{Applied Soft Computing}},
  keywords     = {{Algorithm selection, Combinatorial optimization, Multi-objective optimization, Performance measurement, Traveling Salesperson Problem}},
  number       = {{C}},
  title        = {{{A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms}}},
  doi          = {{10.1016/j.asoc.2019.105901}},
  volume       = {{88}},
  year         = {{2020}},
}

@article{46334,
  abstract     = {{We build upon a recently proposed multi-objective view onto performance measurement of single-objective stochastic solvers. The trade-off between the fraction of failed runs and the mean runtime of successful runs – both to be minimized – is directly analyzed based on a study on algorithm selection of inexact state-of-the-art solvers for the famous Traveling Salesperson Problem (TSP). Moreover, we adopt the hypervolume indicator (HV) commonly used in multi-objective optimization for simultaneously assessing both conflicting objectives and investigate relations to commonly used performance indicators, both theoretically and empirically. Next to Penalized Average Runtime (PAR) and Penalized Quantile Runtime (PQR), the HV measure is used as a core concept within the construction of per-instance algorithm selection models offering interesting insights into complementary behavior of inexact TSP solvers.}},
  author       = {{Bossek, Jakob and Kerschke, Pascal and Trautmann, Heike}},
  issn         = {{1568-4946}},
  journal      = {{Applied Soft Computing}},
  keywords     = {{Algorithm selection, Multi-objective optimization, Performance measurement, Combinatorial optimization, Traveling Salesperson Problem}},
  pages        = {{105901}},
  title        = {{{A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms}}},
  doi          = {{https://doi.org/10.1016/j.asoc.2019.105901}},
  volume       = {{88}},
  year         = {{2020}},
}

@article{54004,
  author       = {{Sodenkamp, Mariya A. and Tavana, Madjid and Di Caprio, Debora}},
  issn         = {{1568-4946}},
  journal      = {{Applied Soft Computing}},
  pages        = {{715--727}},
  publisher    = {{Elsevier BV}},
  title        = {{{An aggregation method for solving group multi-criteria decision-making problems with single-valued neutrosophic sets}}},
  doi          = {{10.1016/j.asoc.2018.07.020}},
  volume       = {{71}},
  year         = {{2018}},
}

@article{54172,
  author       = {{Mousavi, Seyed Mohsen and Sadeghi, Javad and Niaki, Seyed Taghi Akhavan and Tavana, Madjid}},
  issn         = {{1568-4946}},
  journal      = {{Applied Soft Computing}},
  pages        = {{57--72}},
  publisher    = {{Elsevier BV}},
  title        = {{{A bi-objective inventory optimization model under inflation and discount using tuned Pareto-based algorithms: NSGA-II, NRGA, and MOPSO}}},
  doi          = {{10.1016/j.asoc.2016.02.014}},
  volume       = {{43}},
  year         = {{2016}},
}

@article{54170,
  author       = {{Khanjani Shiraz, Rashed and Fukuyama, Hirofumi and Tavana, Madjid and Di Caprio, Debora}},
  issn         = {{1568-4946}},
  journal      = {{Applied Soft Computing}},
  pages        = {{204--219}},
  publisher    = {{Elsevier BV}},
  title        = {{{An integrated data envelopment analysis and free disposal hull framework for cost-efficiency measurement using rough sets}}},
  doi          = {{10.1016/j.asoc.2016.04.043}},
  volume       = {{46}},
  year         = {{2016}},
}

@article{54165,
  author       = {{Khalili-Damghani, Kaveh and Tavana, Madjid and Santos-Arteaga, Francisco J.}},
  issn         = {{1568-4946}},
  journal      = {{Applied Soft Computing}},
  pages        = {{676--702}},
  publisher    = {{Elsevier BV}},
  title        = {{{A comprehensive fuzzy DEA model for emerging market assessment and selection decisions}}},
  doi          = {{10.1016/j.asoc.2015.09.048}},
  volume       = {{38}},
  year         = {{2016}},
}

@article{54156,
  author       = {{Tavana, Madjid and Zareinejad, Mohsen and Di Caprio, Debora and Kaviani, Mohamad Amin}},
  issn         = {{1568-4946}},
  journal      = {{Applied Soft Computing}},
  pages        = {{544--557}},
  publisher    = {{Elsevier BV}},
  title        = {{{An integrated intuitionistic fuzzy AHP and SWOT method for outsourcing reverse logistics}}},
  doi          = {{10.1016/j.asoc.2015.12.005}},
  volume       = {{40}},
  year         = {{2016}},
}