Portfolio optimization is an activity for balancing return and risk. In this paper, we used mean-variance (M-V) portfolio models with buy-in threshold and cardinality constraints. This model can be formulated as a mixed integer nonlinear programming (MINLP) problem. To solve this constrained...

Actors in various settings have been increasingly relying on algorithmic tools to support their decision-making. Much of the public debate concerning algorithms - especially the associated regulation of new technologies - rests on the assumption that humans can assess the quality of algorithms....

Due to the increasing price pressure in the less-than-truckload (LTL) market, horizontal cooperation is an effective and efficient way for small- and medium-sized LTL carriers to enhance their profits by exchanging requests. For this purpose, a decentralized auction-based collaboration framework...

Optimization is an act of decision-making for reaching a point in which the overall behaviour of the considered system is acceptable by the experts. In this paper, the optimum design of truss structures is considered utilizing the Material Generation Algorithm (MGA) as one of the recently...

In this paper, optimum design of building structures is conducted by metaheuristic algorithms due to the shortcomings of the conventional design methods in providing economical designs. The Harmony Search (HS) is utilized as the main algorithm which was developed based on the musical process of...

Machine learning (ML) is a new-age thriving technology, which facilitates computers to read and interpret from the previously present data automatically. It makes use of multiple algorithms to build models, mathematical in nature, and then makes predictions for the new data using the past data...