LINGO is a comprehensive tool designed to make building and solving Linear, Nonlinear (convex & nonconvex/Global), Quadratic, Quadratically Constrained, Second Order Cone, Stochastic, and Integer optimization models faster, easier and more efficient. LINGO provides a completely integrated package that includes a powerful language for expressing optimization models, a full featured environment for building and editing problems, and a set of fast built-in solvers

References in zbMATH (referenced in 253 articles )

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  1. Chang, Jiyoun C.; Graves, Stephen C.; Kirchain, Randolph E.; Olivetti, Elsa A.: Integrated planning for design and production in two-stage recycling operations (2019)
  2. Das, Amrit; Bera, Uttam Kumar; Maiti, Manoranjan: Defuzzification and application of trapezoidal type-2 fuzzy variables to Green solid transportation problem (2018)
  3. Gupta, Srikant; Ali, Irfan; Ahmed, Aquil: Multi-objective capacitated transportation problem with mixed constraint: a case study of certain and uncertain environment (2018)
  4. Lancia, Giuseppe; Serafini, Paolo: Compact extended linear programming models (2018)
  5. Mehdizadeh, Esmaeil; Niaki, Seyed Taghi Akhavan; Hemati, Mojtaba: A bi-objective aggregate production planning problem with learning effect and machine deterioration: modeling and solution (2018)
  6. Sun, Yan; Hrušovský, Martin; Zhang, Chen; Lang, Maoxiang: A time-dependent fuzzy programming approach for the green multimodal routing problem with rail service capacity uncertainty and road traffic congestion (2018)
  7. Chen, Huey-Kuo: A heuristic for the doubly constrained entropy distribution/assignment problem (2017)
  8. Fendl, Hannes; Neumaier, Arnold; Schichl, Hermann: Certificates of infeasibility via nonsmooth optimization (2017)
  9. Jindal, Anil; Sangwan, Kuldip Singh: Multi-objective fuzzy mathematical modelling of closed-loop supply chain considering economical and environmental factors (2017)
  10. Kundu, Pradip; Kar, Mouhya B.; Kar, Samarjit; Pal, Tandra; Maiti, Manoranjan: A solid transportation model with product blending and parameters as rough variables (2017)
  11. Lu, Hao-Chun: Improved logarithmic linearizing method for optimization problems with free-sign pure discrete signomial terms (2017)
  12. Paul, Sanjoy Kumar; Sarker, Ruhul; Essam, Daryl: A quantitative model for disruption mitigation in a supply chain (2017)
  13. Rizk-Allah, R. M.; Abo-Sinna, Mahmoud A.: Integrating reference point, Kuhn-Tucker conditions and neural network approach for multi-objective and multi-level programming problems (2017)
  14. Baidya, Abhijit; Bera, Uttam Kumar; Maiti, Manoranjan: Multi-stage multi-objective solid transportation problem for disaster response operation with type-2 triangular fuzzy variables (2016)
  15. Baidya, Abhijit; Bera, Uttam Kumar; Maiti, Manoranjan: The grey linear programming approach and its application to multi-objective multi-stage solid transportation problem (2016)
  16. Borraz-Sánchez, Conrado; Bent, Russell; Backhaus, Scott; Hijazi, Hassan; Van Hentenryck, Pascal: Convex relaxations for gas expansion planning (2016)
  17. Chen, Shih-Pin: Time value of delays in unreliable production systems with mixed uncertainties of fuzziness and randomness (2016)
  18. Deep, Kamal; Singh, Pardeep K.: Dynamic cellular manufacturing system design considering alternative routing and part operation tradeoff using simulated annealing based genetic algorithm (2016)
  19. Gassmann, Horand; Ma, Jun; Martin, Kipp: Communication protocols for options and results in a distributed optimization environment (2016)
  20. Giri, Pravash Kumar; Maiti, Manas Kumar; Maiti, Manoranjan: Profit maximization solid transportation problem under budget constraint using fuzzy measures (2016)

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