Gino K. Yang

Inventory models with variable lead time and present value

The figures for inventory make up a huge proportion of a companys working capital. Because of this, we formulated the optimal replenishment policy considering the time value of money to represent opportunity cost. In this article, we provide a mixed inventory model, in which the distribution of lead time demand is normal, to consider the time value. First, the study tries to find the optimal reorder point and order quantity at all lengths of lead time with components crashed to their minimum duration. Secondly, we develop a method to insure the uniqueness of the reorder point to locate the optimal solution. Finally, some numerical examples are given to illustrate our findings.

Note on sensitivity analysis of inventory model with partial backorders

Abstract In reality, most of the values used for estimating future inventory are parameters derived from the present inventory model. Therefore, researchers must consider how changes in related environments will impact these parameters. A sensitivity analysis explores the impact on the optimal solution when the parameter values vary. This note extends Chu and Chung’s [European Journal of Operational Research 152 (2004) 289–295] paper for the sensitivity analysis of the inventory model with partial backorders. We found the criterion for determining when to run the inventory system. This new discovery deserves careful examination. Numerical examples are provided to demonstrate our findings.

Solution Structure for an Analytic Model of Bus Service Zones

This paper points out questionable derivations for the formulated solution in the algebraic approach for the optimal length of local bus route of a traffic model for bus service zones. It also provides revisions for the algebraic approach to prove the existence and uniqueness for the formulated optimal solution. An iterative method was then applied to obtain an alternative sequence that converges to the optimal solution. The same numerical examples in the literature are examined to support the findings.

Fitting Lanchester's square law to the Ardennes Campaign

In this research, we try to improve Brackens and Chens work to significantly better fit our extended Lanchester model into the Ardennes Campaign live data. Essentially, we adopt the concepts of the tactical factor variable and the shift time variable to improve the original Lanchesters model. Moreover, we use the Lanchester square law model instead of Lanchester linear law model to reflect the fact that the Ardennes Campaign was not an indirect-fire but a direct-fire combat. According to our numerical experimental result, we improved Brackens work by 39.26%, and Chens work by 19.51%. The contribution of this research is that we propose a much better qualitative analysis model for the explanation of modern combat.

An improved algorithm for the minimax distribution-free inventory model with incident-oriented shortage costs

This article reconsiders Gallegos minimax distribution-free procedure. He created a two-point distribution to serve the most unfavorable case for estimating the expected cost of lost sales. We provide a reasonable condition to insure the existence and uniqueness of the optimal solution and the convergence of Gallegos method.

Adopting Lanchester Model to the Ardennes Campaign with Deadlock Situation in the Shift Time between Defense and Attack

General Karl Von Clausewitz believes that attack and defense in warfare are a state of interaction and response. The shift between attack and defense is involved with a short span of time difficult to define in concrete format. This paper extends Chen and Chus model of the Ardennes campaign of World War II using the Lanchester equations. We use a new variable, deadlocked situation, to represent the shifting time between attack and defense. This article divides the Ardennes Campaign into three periods: (a) the initial period, German attacked while the Allies defended; (b) the middle period, both sides seized the initiative; (c) the final period, Allies attacked while Germans defended. In this paper, we apply Lanchesters Square Law to estimate the casualties by determining the shifting time between attack and defense. We obtain improved goodness of fit for the historical data.

The battle of Gibeah: a further analysis

This paper studies the battle of Gibeah that happened three thousand years ago between the tribe of Benjamin and the other eleven tribes of Israel. In 1995, in the journal of Naval Research Logistics, David modeled this battle. We examine the assumptions of Davids paper to derive the following results: (1) the number of the inhabitances of Gibeah; (2) in the first two days of the battle, there are no casualty of slinger; (3) the battle duration time is a new decision variable. From our finding, it provides a sounded base for the further development for a new heterogeneous Lanchester model for the battle of Gibeah.

TECHNICAL NOTE: APPROXIMATION SOLUTION FOR THE INVENTORY MODEL WITH RANDOM PLANNING HORIZON

In 1993, Moon and Yun [8] developed a finite planning horizon economic order quantity (EOQ) model by using the Discounted Cash Flow approach. Chung and Lin [3] then improved Moon and Yuns solution by introducing a pair of closer lower and upper bounds and bisection algorithm. To avoid the unnecessary and time-consuming numerical computations, we propose a novel approach in this paper to calculate the optimal solution of the same problem by using an accurate and efficient approximation solution directly without any further iterative numerical computations such as the bisection algorithm.