This paper investigates reward expiry for loyalty programs. It provides insights into the profitability of setting reward expiry for competing firms and identifies conditions under which such a policy would be beneficial. We develop and solve a stochastic model that reflects consumer behavior in...

In this study, we analyze the challenges faced by manufacturers in promoting sustainability throughout their supply chains when the supplier is capital-constrained, has private access to production cost information, and must choose between regular and sustainable production. We develop a dyadic...

This thesis studies a single item periodic review inventory problem with stochastic demand, random price and quotation cost. It differs from the traditional inventory model in that at the beginning of each period, a decision is made whether to pay the quotation cost to get the price information....

This research focuses on Markov Decision Processes (MDP). MDP is one of the most important and challenging areas of Operations Research. Every day people make many decisions: today's decisions impacttomorrow's and tomorrow's will impact the ones made the day after. Problems in Engineering,...

This paper addresses a hub-and-spoke network problem for railroad freight, where a central planner is to find transport routes, frequency of service, length of trains to be used, and transportation volume. Hub-and-spoke networks, often found in air freight, have not been favoured by railways in...

We examine the hypothesis that the concept of symmetry augmentation is fundamentally linked to learning. Our focus in this study is on the augmentation of symmetry embedded in 1-dimensional time series (1D-TS). Motivated by the duality between 1D-TS and networks, we augment the symmetry by...

Reinforcement learning (RL) for dynamic asset allocation is an emerging field of study. Total return, the common performance metric, is useful for comparing algorithms but does not help us determine how close an RL algorithm is to an optimal solution. In real world financial applications, a bad...