Ruwen Qin

A Real Options Model for Workforce Cross-Training

Abstract In this article, we propose using a real options framework to model and financially value a cross-training policy. The cross-training policy involves a dynamic investment on workforce flexibility. We model it as an approximation of an American call option using binomial lattices. Value stems from the merit of dynamic cross-training compared with the deterministic case using traditional discounted cash flow techniques. This work is discussed in the context of a volatile production system characterized by product dynamics, labor dynamics, task heterogeneity and workforce heterogeneity. Results suggest that cross-training based on the real options approach is dependent on the production capability and the level of workforce heterogeneity. Thus, valuing workforce flexibility using real options has strategic utility beyond that of the net present value approach.

Optimal crude oil procurement under fluctuating price in an oil refinery

In this paper, we study the optimal procurement and operation of an oil refinery. The crude oil prices follow geometric Brownian motion processes with correlation. We build a multiperiod inventory problem where each period involves an operation problem such as separation or blending. The decisions are the amount of crude oils to purchase and the amount of oil products to produce. We employ approximate dynamic programming methods to solve this multiperiod multiproduct optimization problem. Numerical results reveal that this complex problem can be approximately solved with little loss of optimality. Further, we find that the approximate solution significantly outperforms a set of myopic policies that are currently used.

An optimal plan of zero-defect single-sampling by attributes for incoming inspections in assembly lines

This paper proposes a nonlinear integer program for determining an optimal plan of zero-defect, single-sampling by attributes for incoming inspections in assembly lines. Individual parts coming to an assembly line differ in the non-conforming (NC) risk, NC severity, lot size, and inspection cost-effectiveness. The proposed optimization model is able to determine the inspection sample size for each of the parts in a resource constrained condition where a product’s NC risk is not a linear combination of NC risks of the individual parts. This paper develops a three-step solution procedure that effectively reduces the solution time for larger size problems commonly seen in assembly lines. The proposed optimization model provides insightful implications for quality management. For example, it reveals the principle of sample size decisions for heterogeneous, dependent parts waiting for incoming inspections; as well as provides a tool for quantifying the expected return from investing additional inspection resources. The optimization model builds a foundation for extensions to advanced inspection sampling plans.

Real options as an incentive scheme for managing revenues in transportation infrastructure projects

Revenue management for transportation infrastructure projects is challenging due to the huge amount of capital involved and the deep uncertainty inherent in long service lifetimes. Public-private partnerships (PPPs) provide a way for the public sector to acquire financial resources and transfer risks in such projects. This paper proposes a real options (ROs) incentive to improve revenue management for PPPs. In addition to the initial concession, the public sector offers an RO incentive to the private sector at a premium. Designed in an option game framework, the RO incentive captures the behaviour dynamics of option owner and writer, thus producing an optimal strategy for revenue management that cannot be derived from the standard RO valuation. The RO incentive stimulates the private sector to increase its investment in quality improvement, makes a short concession attractive to the private sector and allows both parties to better manage revenues under high uncertainty.

A Framework of Cost-Effectiveness Analysis for Alternative Energy Strategies

Abstract: Strategies for implementing alternative energy sources are drawing growing attention as global environmental and other challenges raise concerns over energy consumption. Cost-effectiveness is an important criterion for assessing strategy applicability. Currently, few economic studies have been performed on alternative energy in a systematic approach. Thus, this article establishes a framework for such analysis that summarizes a consensus of anticipated changes resulting from the use of representative alternative energy types and presents an adaptive scheme of cost estimation. Consequently, it is able to provide a basis for systematic cost-effectiveness analysis of alternative strategy research and practice. A case study developed as part of this research project demonstrates the functionality of the framework and shows how it assists engineering managers, policy makers, and investors in asset acquisition, strategy deployment, or operations and maintenance.

Double-sided price adjustment flexibility with a preemptive right to exercise

This paper proposes a double-sided flexibility in adjusting the lease price as an alternative, more accessible tool for managing revenues or controlling costs in volatile markets. The double-sided flexibility addresses the dilemma of allowing only one party of a lease contract to have the price adjustment flexibility while both parties want it. Although the proposed clause grants both contract parties the right to adjust the lease price for one time during the contract life, one party can enjoy superior flexibility over the counterparty by buying a preemptive right to exercise it. The paper models the double-sided flexibility as sequentially compounded real options and optimizes the exercise decision for each option owner. The proposed flexibility clause is embedded in time charter contracts in the maritime transport industry to illustrate the effectiveness of it in helping manage the price risk of lease contracts.

Track fast-moving tiny flies by adaptive LBP feature and cascaded data association

Studying the behavior of fruit flies that mimic normal animal motivations can inform us about the molecular mechanisms and biochemical pathways. We build a glass chamber to house flies and record their behaviors in video frame sequences. Due to the challenges of low image contrast, small object size and fast object motion, we propose an adaptive Local Binary Pattern (LBP) feature to detect flies and develop a cascaded data association approach with fine-to-coarse gating region control to track flies in the spatio-temporal domain. Our approach is validated on two long video sequences with very good performance, showing its potential to enable automated characterization of biological processes.

Valuation of Lease Contracts with a Price Adjustment Option: An Application to the Maritime Transport Industry

In volatile lease markets, a fixed rate contract may allow one contract party to gain excessive profits while letting the other party face substantial losses. The flexibility in adjusting the contract rate can help address this issue and maintain a fair long-term relationship. This article models and prices the flexibility using real options and derives the boundary of option exercise to facilitate the optimal decision on the rate adjustment. The proposed method is applied to time charter contracts in the maritime transport industry. Moreover, the level of flexibility can be tailored to meet different budgets for the flexibility.

A Contract Negotiation Model for Constituent Systems in the Acquisition of Acknowledged System of Systems

In the acquisition of acknowledged system of systems (SoSs), the SoS manager attempts to reach a coalition agreement with each of selected constituent systems. When the systems have self-interests that are incompatible with the SoS’s goal, contract negotiation is a way of resolving conflicts. Complexity of the acknowledged SoS acquisition makes the negotiation a hard decision process for constituent systems. To the SoS manager, the negotiation with consistent systems is difficult too, considering that the behavior and strategies of constituent systems in negotiation impact the ability and timeliness of a group to agree on an SoS architecture, and so the overall mission effectiveness of the SoS. Motivated by these, this paper develops a contract negotiation model for constituent systems in the acknowledged SoS acquisition. The model consists of: 1) a protocol for negotiating multiple interdependent issues of multiple items over multiple stages and 2) a decision framework of constituent systems. The model is not only a decision support for constituent systems but also a tool with which the SoS manager can better understand constituent systems.

Evaluating Useful Life and Developing Replacement Schedules for LED Traffic Signals: Statistical Methodology and a Field Study

Abstract: LEDs (light-emitting diodes) have been widely adopted for use within traffic signals, recently replacing incandescent bulbs. LEDs degrade slowly – unlike incandescent bulbs that fail catastrophically. When the luminous intensity of LEDs falls below a pre-specified threshold, they pose danger to traffic. The long-term performance and degradation rates of LEDs have not been thoroughly studied in order to gain an understanding of their useful lives and appropriate replacement schedules. There exist many stochastic factors that affect LED degradation rates making their analysis complicated. This article provides a statistical methodology based on ordinary least-squares regression for measuring the useful life and the degradation rate of an LED signal, and presents details from a field study conducted in Missouri, U.S. Our results indicated that signal type, color, and manufacturer affect degradation, and therefore useful life should be calculated for each subgroup of LED traffic signals separately. Results of this research provide a much needed methodology for engineering managers in departments of transportation and local communities for replacing LEDs.