Optimal machine capacity expansions with nested limitations under stochastic demand

This paper studies capacity expansions for a production facility that faces uncertain customer demand for a single product family. The capacity of the facility is modeled in three tiers, as follows. The first tier consists of a set of upper bounds on production that correspond to different resource types (e.g., machine types, categories of manpower, etc.). These upper bounds are augmented in increments of fixed size (e.g., by purchasing machines of standard types). There is a second‐tier resource that constrains the first‐tier bounds (e.g., clean room floor space). The third‐tier resource bounds the availability of the second‐tier resource (e.g., the total floor space enclosed by the building, land, etc.). The second and third‐tier resources are expanded at various times in various amounts. The cost of capacity expansion at each tier has both fixed and proportional elements. The lost sales cost is used as a measure for the level of customer service. The paper presents a polynomial time algorithm (FIFEX) to minimize the total cost by computing optimal expansion times and amounts for all three types of capacity jointly. It accommodates positive lead times for each type. Demand is assumed to be nondecreasing in a “weak” sense. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

Dual sourcing: Responsive hedging against correlated supply and demand uncertainty

This article analyzes dual sourcing decisions under stochastically dependent supply and demand uncertainty. A manufacturer faces the trade‐off between investing in unreliable but high‐margin offshore supply and in reliable but low‐margin local supply, where the latter allows for production that is responsively contingent on the actual demand and offshore supply conditions. Cost thresholds for both types of supply determine the optimal resource allocation: single offshore sourcing, single responsive sourcing, or dual sourcing. Relying on the concept of concordance orders, we study the effects of correlation between supply and demand uncertainty. Adding offshore supply to the sourcing portfolio becomes more favorable under positive correlation, since offshore supply is likely to satisfy demand when needed. Selecting responsive capacity under correlated supply and demand uncertainty is not as straightforward, yet we establish the managerially relevant conditions under which responsive capacity either gains or loses in importance. Our key results are extended to the broad class of endogenous supply uncertainty developed by Dada et al. [Manufact Serv Operat Mange 9 (2007), 9–32].© 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

The “motivated bias” dilemma in warfare and intelligence

The goal of this article is to challenge the assumption of rationality in the behavior of decision-making units involved in security, defense, intelligence and warfare and to consider the influence of “motivated bias” in such instances. A review of motivational literature within international politics and a discussion of literature applying “motivated biases” to warfare and strategic surprise will offer an alternative view of the primacy of rationality in such decisions.     

Involving the elephant: technical isolation and the role of India in a possible solution to the Iranian nuclear crisis

Apart from North Korea, no state's nuclear program in the twenty-first century has raised more concern to international security than Iran's. While Iran insists that its nuclear program is strictly for civilian purpose in line with Article IV of non-proliferation treaty, the USA and its allies insist that Iran has military intentions and called for sanctions. The failure of sanctions to deter Iran from its nuclear agenda had made many scholars and policy-makers call for a preemptive attack on Iranian nuclear facilities. Situated within this debate, this paper positions itself as an antagonist to the preemptive airstrike option and argues that involving India in a possible nuclear “iron curtain” against Iran – a move known as technical isolation – remains the best option to the current nuclear crises.     

Technical note: Finite-time regret analysis of Kiefer-Wolfowitz stochastic approximation algorithm and nonparametric multi-product dynamic pricing with unknown demand

We consider the problem of nonparametric multi-product dynamic pricing with unknown demand and show that the problem may be formulated as an online model-free stochastic program, which can be solved by the classical Kiefer-Wolfowitz stochastic approximation (KWSA) algorithm. We prove that the expected cumulative regret of the KWSA algorithm is bounded above by where κ₁, κ₂ are positive constants and T is the number of periods for any T = 1, 2, … . Therefore, the regret of the KWSA algorithm grows in the order of , which achieves the lower bounds known for parametric dynamic pricing problems and shows that the nonparametric problems are not necessarily more difficult to solve than the parametric ones. Numerical experiments further demonstrate the effectiveness and efficiency of our proposed KW pricing policy by comparing with some pricing policies in the literature.     

Managerial inventory formulations with stockout objectives and fiscal constraints

Most inventory formulations seek to minimize the sum of ordering costs, holding costs, and stockout costs: however, management often directs inventory policy by specifying a maximum investment level and/or a purchasing budget constraint. Within these limitations, they expect lower level managers to optimize some level of customer satisfaction, such as minimum stockouts or minimum shortages. The author has developed several cases of these “managerial” inventory formulations and has presented some computational results.