Managing the Balance Between Project Value and Net Present Value Using Reinforcement Learning

Project managers make decisions weighing financial returns (net present value, NPV) and value creation expected by stakeholders. Often, plans maximizing NPV neglect stakeholder benefits while those focused strictly on value creation may reduce financial viability. This paper puts forth a new stochastic optimization model handling this compromise using a mixed integer program solved with reinforcement learning. The model incorporates uncertain activity durations and considers positive and negative cash flows. Our Monte Carlo control method with $\epsilon$ -greedy policies and timed start actions for activities facilitates the simultaneous maximization of NPV and project value. The resulting efficient frontier delineates various project plans, demonstrating the trade-off between maximizing NPV and project value, providing decision makers with visual analysis to select plans that fit organizational needs. Computational experiments demonstrate superior performance over a mathematical solver limited by the problem’s complexity and a metaheuristic lacking guided online learning. The results help senior management select satisfactory plans that balance financial returns with stakeholder preferences. The methodology contributes a novel tool for quantitatively incorporating value creation alongside financial objectives in project planning

Optimal Parallel Inspection for Finding the First Nonconforming Unit in a Batch---An Information Theoretic Approach

We consider the case of a batch of discrete units produced by a process subject to failures under a known probability distribution function, and apply information theory to the problem of finding the first nonconforming unit in the batch at minimum cost. Two distinct but related aspects of this problem were treated: determining which units should be inspected, and determining how many units should be sent for inspection at the same time. The solution is based on the principles of inspecting the product units that maximize the reduction in the uncertainty regarding the location of the first nonconforming unit, and of minimizing the cost per unit of uncertainty reduced. These principles are formalized by means of a series of theorems leading to an easy-to-implement algorithm for managing parallel inspection. This approach is successfully compared with the optimal solution obtained with dynamic programming and with other heuristics.inspection planning, information theory

Integrating the Number and Location of Retail Outlets on a Line with Replenishment Decisions

We research the management approach that quantitatively combines decisions that affect different planning horizons--namely, the strategic and operational ones--and simultaneously derive the optimal values of these decisions. The system we investigate comprises retail outlets and customers in an infinite-horizon setting. Both retail outlets and customers are located on a finite homogenous line segment. The total demand posed by customers is normally distributed with known mean and variance. To optimally design and operate such a system, we need to determine the optimal values of the number of retail outlets, the location of each retail outlet, and the replenishment inventory levels maintained at each retail outlet. We analyze the system from an expected cost point of view, considering the fixed costs of operating the retail outlets, the expected holding and shortage costs, and the expected delivery costs. We show that all decisions can be represented as a function of the number of retail outlets. Moreover, we show that the system's expected cost function is quasi-convex in the number of retail outlets. We compare our model to a model that does not integrate these decisions at once. We show the advantage of our approach on both the solution and objective spaces. We propose an exact quantification of this advantage in terms of the cost and problem parameters. In addition, we point out several managerial insights.location-inventory model, implicit function theorem, risk pooling, infinite-horizon stochastic inventory, subadditive function, quasi-convex