The timeliness of blood supply in the aftermath of a catastrophic event is critical for saving lives. Using historical earthquakes data from Iran, this paper posits and numerically illustrates a fuzzy optimization model to minimize the overall blood supply duration from donation time to the time...

Conventional data envelopment analysis (DEA) models cannot deal with negative and uncertain values. Accordingly, the main objective of current study is to present a novel robust data envelopment analysis (RDEA) approach that is capable to be used in the presence of negative values and uncertain...

The linear ordering problem (LOP), which consists in ordering M objects from their pairwise comparisons, is commonly applied in many areas of research. While efforts have been made to devise efficient LOP algorithms, little was done to verify if the obtained solutions are valid and thus if they...

This paper examines how to design the sustainable production line in the factories with minimum environmental impacts and maximum social benefits. For modeling, the literature review is carried out first and according to researches and papers, environmental and social factors are extracted and...

The uncapacitated facility location problem (UFLP) is a real-world binary optimization problem that aims to find the number of opened facilities that minimizes the total cost of exchange between customer and facilities and opening cost of these facilities. UFLP is in class of NP-Hard and, there...

This review article is intended to collect and summarize many of the results in the field of optimal execution over the last twenty years. In doing so, we describe the general workings of the limit order book so that the sources of costs and risks which need to be optimized are understood. The...

We propose an actor-critic reinforcement learning (RL) algorithm for the optimal execution problem. We consider the celebrated Almgren-Chriss model in continuous time and formulate a relaxed stochastic control problem for execution under an entropy regularized mean-quadratic variation objective....

We overcome an obstacle in mathematical optimization. In so doing, we explicitly derive the optimal values without assuming the smoothness of the value function. We apply our method to the portfolio model