The purpose of this study is to address the critical issue of optimal credit allocation. Predicting a borrower's probability of default is a key requirement of any credit allocation system but turning it into labeled classes leads to problems in performance measurement. In this paper the...

Maritime transportation is preferred over other transportation forms for trade and has seen a significant increase worldwide. One of the problems that often occur in maritime transportation is the high cost because vessels' availability and capacity will always be the same while the demand tends...

Quantity and price risks determine key uncertainties market participants face in electricity markets with increased volatility, for instance due to high shares of renewables. In the time from day-ahead until real-time, there lies a large variation in best available information, such as between...

We propose a new method for solving high-dimensional dynamic programming problems and recursive competitive equilibria with a large (but finite) number of heterogeneous agents using deep learning. The "curse of dimensionality" is avoided due to four complementary techniques: (1) exploiting...

The rapid development of artificial intelligence methods contributes to their wide applications for forecasting various financial risks in recent years. This study introduces a novel explainable case-based reasoning (CBR) approach without a requirement of rich expertise in financial risk....

The effectiveness and efficiency of optimization algorithms might deteriorate when solving large-scale binary integer programs (BIPs). Consequently, researchers have tried to fix the values of certain variables called adjunct variables, and only optimize a small problem version formed from the...

Data Envelopment Analysis (DEA) has been widely applied in measuring the efficiency of Decision-Making Units (DMUs). The conventional DEA has three major drawbacks: a) it does not consider Decision Makers’ (DMs) preferences in the evaluation process, b) DMUs in this model are flexible in...

In studying petroleum supply chain networks, past studies have largely segregated three critical decision-making aspects: integrated planning, uncertainties, and multi-objective setting. This study focuses on consolidating these aspects and proposes a stochastic, multi-objective, mixed-integer...

Many current problems in air traffic are related to the number of aircraft movements. Overcrowding in the airspace, difficult coordination at airports, high emissions of noise and pollutants as well as complexity of airlines are side effects of too many aircraft movements. This study examines...

In this paper, we describe a novel iterative procedure called SISTA to learn the underlying cost in optimal transport problems. SISTA is a hybrid between two classical methods, coordinate descent ("S"-inkhorn) and proximal gradient descent ("ISTA"). It alternates between a phase of exact...

Purpose: The purpose of this paper is to study the Manufacturers pallet-loading problem (MPLP), by loading identical small boxes onto a rectangle pallet to maximise the pallet utilization percentage while reducing the Complexity of loading. Design/methodology/approach: In this research a Block...

Due to recent technical progress, battery energy storages are becoming a viable option in the power sector. Their optimal operational management focuses on load shift and shaving of price spikes. However, this requires optimally responding to electricity demand, intermittent generation, and...

Rust (1987) concludes that the data "clearly reject" the hypothesis that Harold Zurcher made bus replacement decisions using a monthly (and myopic) discount rate of 0 in favor of the factor 0.9999. The alternative model requires the nested fixed point algorithm developed in the paper which...