METHODOLOGIES AND APPLICATION Framework selection for developing optimization algorithms: assessing preferences by conjoint analysis and best–worst method Gulin Zeynep Oztas 1 • Sabri Erdem 2 Ó Springer-Verlag GmbH Germany, part of Springer Nature 2020 Abstract In recent years, the evolutionary algorithms used in the solution of NP-Hard problems have become increasingly important. In addition, platforms and application development languages have diversified and started to be differentiated according to their intended use. However, the selection of an appropriate model development environment has become an important decision problem. This study guides the selection of suitable tools for optimization problems, especially in management science. The main objective is to identify the key attributes of the frameworks from the researcher’s point of view in management science and assign a total utility score to measure the relative importance of frameworks for evolutionary algorithms. For that reason, we propose a conjoint analysis model upon the preferences of management scientist for the appropriate framework that meets the needs in optimization problems. We also aim at providing effective usage of relevant frameworks for appropriate types of problems, facilitating the work of researchers and therefore increasing the quality of the optimization procedure. By doing so, losing time and effort resulting from the wrong platform and framework selection, as well as ineffective model results, will be avoided. Moreover, the frameworks are also evaluated by calculating the weights of criteria with one of the recent multi-criteria decision-making method called Euclidean best–worst method and compared with the findings obtained from conjoint analysis. This study not only provides review of existing software tools developed for optimization problems but also contributes to research and practice in the field of optimization algorithms in general and helps the researchers in management science for meeting their needs while searching for the appropriate framework. Keywords Framework selection  Conjoint analysis  Optimization  Multi-criteria decision making  Euclidean best–worst method 1 Introduction In the field of management science, as the optimization problems become more complex, the methods presented for the solution of these problems are still developing. As parallel to the improvements in computer technology, iterative and divide-and-conquer-based methods gained extra importance and therefore, heuristics played an important role because of not all the problems that cannot be concluded by rules in the algebraic way. Most real-world problems are NP-Hard that cannot be solved in polynomial time (Sotoudeh-Anvari and Hafeza- lkotob 2018). For this reason, in recent years, the evolu- tionary algorithms used to solve NP-Hard problems have become increasingly important. Some of the pioneers of evolutionary algorithms can be summarized as follows: Genetic Algorithm (Holland 1962), Simulated Annealing Communicated by V. Loia. Only the abstract was submitted to the ‘‘20th International Symposium on Econometrics, Operations Research and Statistics’’ for oral presentation. & Gulin Zeynep Oztas gzeynepa@pau.edu.tr Sabri Erdem sabri.erdem@deu.edu.tr 1 Department of Business Administration, Pamukkale University, 20160 Denizli, Turkey 2 Department of Business, Dokuz Eylul University, 35390 Izmir, Turkey 123 Soft Computing https://doi.org/10.1007/s00500-020-05411-8