We have listed and described some numerical methods and techniques for the reader so that he can be acquainted with them and then a description program flow chart is mentioned without the Matlab Software Program. Here, the Matlab Software Program for the Methods and Algorithms mentioned in. The...

A growing number of emerging studies have been undertaken to examine the mediating dynamics between intelligent agents, activities, and cost within allocated budgets, in order to predict the outcomes of complex projects in dint of their significant uncertain nature in achieving a successful...

Introduction. Dynamic Economic Emission Dispatch is the extended version of the traditional economic emission dispatch problem in which ramp rate is taken into account for the limit of generators in a power network. Purpose. Dynamic Economic Emission Dispatch considered the treats of economy and...

Machine Learning algorithms are becoming widely deployed in real world decision-making. Ensuring fairness in algorithmic decision-making is a crucial policy issue. Current legislation ensures fairness by barring algorithm designers from using demographic information in their decision-making. As...

We develop a jump-diffution model for a guarantee-investment combination financing mode (G-I mode) that is recently popular in financial practice. We assume that a borrower has exclusively an option to invest in a project in two stages. The project's cash flow follows a double exponential...

We employ reinforcement learning (RL) techniques to devise statistical arbitrage strategies in electronic markets. In particular, double deep Q network learning (DDQN) and a new variant of reinforced deep Markov models (RDMMs) are used to derive the optimal strategies for an agent who trades in...

In this paper, we study endogeneity problems in algorithmic decision-making where data and actions are interdependent. When there are endogenous covariates in a contextual multi-armed bandit model, a novel bias (self-fulfilling bias) arises because the endogeneity of the covariates spills over...

This paper addresses a set of active learning problems that occur in the development of liquid biopsies via the lens of active sequential hypothesis testing (ASHT). In the problem of ASHT, a learner seeks to identify the true hypothesis from among a known set of hypotheses. The learner is given...

Prices are increasingly set by algorithms. One concern is that intelligent algorithms may learn to collude on higher prices even in the absence of the kind of coordination necessary to establish an antitrust infringement. However, exactly how this may happen is an open question. I show how in...

We consider continuous-review assemble-to-order (ATO) systems with a general bill of materials (BOM) and general leadtimes. ATO systems have the advantage of mass customization and are widely adopted in practice. However, characterizing the optimal inventory policy is notoriously challenging and...