Chih-Young Hung

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.

Periodic review stochastic inventory models with service level constraint

This article considers the periodic review stochastic inventory models with service level constraint to provide an improved solution procedure. The previous researchers assumed that the objective function is concave down in the lead time so that the minimum must occur on the boundary points of each sub-domain. In this article, we will show that their assumption is questionable since the minimum might not occur at the boundary points of each sub-domain. In a recent paper in International Journal of Systems Science, Ouyang and Chuang studied this problem. However, their solutions contained questionable results and their algorithm might not find the optimal solution due to flaws in their solution procedure. We develop some lemmas to reveal the parameter effects and then present our improved solution procedures for finding the optimal solution for periodic review stochastic inventory models in which the lead time demand is a normal distribution. The savings are illustrated by solving the same examples from Ouyang and Chuangs paper to demonstrate the improvement using our revised algorithm. In the direction of future research, we discuss the comparison between the reordered point being fixed and the reordered point as a new variable.

Global industrial migration: the case of the integrated circuit industry

This paper investigates the global technological migration of the integrated circuit industry from the discovery of semiconductors in 1958 to the founding of a dominant industry model in the late 1980s. The critical turning points we focus on are: 1. the birth of the industry in the USA in the late 1950s; 2. the global change in the business model effected in 1987 by Taiwanese government intervention; 3. the current migration of production capacity to China. Our scope is limited to the USA in discussing the birth and early days of the industry, and to Taiwan in discussing industrial migration. It underscores the role of government and cost reduction in the global migration of the industry. The conclusions of the paper suggest that international technology migration is not an automatic process but the result of specific efforts on the part of the countries involved.

Evaluating development strategies for Taiwan's iB3G industry: a fuzzy MCDM approach

Foreseeing an enormous demand for seamless communication and ubiquitous interconnectivity, Taiwan has launched a national-level dual network program called integrated beyond the third generation (iB3G) to seize the opportunities posed by technological discontinuity. The iB3G initiative aims to leverage Taiwans manufacturing strengths and brand Taiwan as a powerhouse in the creation of integrated cellular/WLAN technologies and services. This paper attempts to secure a consensus on the optimal development strategies and their effective implementation. Our analysis employs a fuzzy multi-criteria decision making (FMCDM) framework with an empirical formula to examine its practicability and usefulness. Based on business, technical and environmental issues, strategies are proffered as follows: (1) shared-value chain and cross-industry collaboration; (2) attractive applications/rich content and service trials on networks; (3) collaborative R&D of multi-mode handsets and integrated network systems; (4) active participation in international standard activities to advance intellectual property; (5) proactive policy tools for business innovation, cultivation of talent and entrepreneurship; (6) supportive regulatory mechanism and sound broadband environment, and (7) promoting the iB3G vision worldwide and asserting leadership. Three clusters are extracted among the seven strategies by fuzzy C-Means approach. Results show that the second strategy receives the highest score.

A Dynamic Competition Simulation for Worldwide Big‐size TV Market Using Lotka‐Volterra Model

Technological innovation is characterized by the substitution of new technologies for full‐fledged ones in the development of new products, processes and techniques. Global TV market is seeing a price down‐spiral for FPD(Flat Panel Display)‐TVs, replacement of CRT by LCD, and consumer’s defection to larger screen. The LCD‐TV market started in Japan from 2003 and took off globally from 2005. LCD panel production is moving toward larger sizes. In the 35″–39″ size market, the price/performance ratio of LCD‐TV is better than that of PDP. The purpose of this paper is to estimate the demand function of worldwide big‐size (35″–39″) TVs including LCD and PDP with an explicit consideration of market competition. The demand function was estimated using Lotka‐Volterra model, a famous competitive diffusion model. The results exhibit a kind of predator‐prey relationship, in which the PDP market was hunted by LCD product. In addition, the coefficients of difference equations of Lotka‐Volterra model in this analysis are...

Application of fuzzy MCDM to priority setting in agricultural biotechnology industries

Abstract Following in the wake of medical biotechnology, agricultural biotechnology (AgBio) is slated to become a key area of development in the biotechnology industry. Because agricultural biotechnology is closely connected with food, health, and resource technology industries, many countries are investing heavily in terms of both funding and talent to enhance their international competitiveness in this field. This research study was designed using the fuzzy multiple criteria decision making (FMCDM) model combining analytic hierarchy process (AHP) and fuzzy theory and holding a specialists’ conference to decide promising AgBio products with international competitiveness for use in guiding industrial development strategies and the allocation of R&D resources. The results show that the FMCDM model can effectively summarize the views of AgBio specialists for the purpose of selecting promising target industries. The research process was also used to explore the various target industries and assess key issues such as the causal relationship between criteria and industries’ degree of development. Beyond helping decision-makers formulate policies and allocate resources, this information is also provided as a research reference in connection with market surveys and industrial development trends, etc.

A Study of A/R Collection for IC Design Industry in Taiwan Using Fuzzy MCDM Methodology

In this paper, we present a fuzzy multiple criteria decision-making (FMCDM) approach to the evaluation of account receivable (A/R) collection instruments. By considering four collection alternatives, namely: the T/T advance (prepayment), the letter of credit (L/C), the documentary collection (including D/A and D/P), and the open account (O/A), the FMCDM approach is for the first time applied to choose the A/R collection instrument for Taiwanese integrated circuit (IC) design industry. Our results show, when face with new customer, the ranking of preference is the T/T advance, the L/C, the O/A and the documentary collection (D/A, D/P). International collection in modern unpredictable global market could be difficult unless firms have taken appropriate collection strategies. We believe that this study provides an alternative for making critical decisions, as in this case, the selection of A/R collection instruments.

An innovative method of project management: a new concept on talent flow

Abstract A concept of innovative management viz. “talent flow” is proposed herein in project management, human resources management and enterprise performance, which originates from extension of “cash flow” of financial management. General enterprises always take the feasibility into evaluation as per the cash flow of the future earnings when deliberation on implementation of or investment in a certain project is conducted; However, as an alternative of financial cash demand, it shall be of necessity to have the know-how support which is called talent flow herein in fulfillment of the project. Know-how is difficultly quantified and it is not easy for enterprises to attain to the optimal input-output ratio in planning and management of human resources, consequently this research is targeted to establish one trial model for talent flow to make simple and rapid analysis of changes of talent flow for project, which shall be the booster for enterprise managers to monitor talent flow and cash flow simultaneously, make real-time reflection of status quo of supply and demand of human resources, promote the efficiency of appointment and dispatch and enhance the enterprise performance and competitiveness in planning or fulfillment of the project plan.

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.

Deploying Arima and Artificial Neural Networks Models to Predict Energy Consumption in Taiwan

With the aim of predicting Taiwan’s energy consumption for the short term (1 year), the medium term (3 years), the medium-long term (5 years), and the long term (10 years), this study applies autoregressive integrated moving average (ARIMA) models and artificial neural networks (ANNs) models and the mean absolute percentage error (MAPE) approach is employed to measure prediction accuracy. Based on data extracted from over the period 1965–2010, the results indicate that the single variable ARIMA models illustrate superior performance than that of ANNs1. As to multivariable models, ANNs8 model including variables of energy consumption and exports show the most accurate prediction in short term and medium-long term, while ANNs6 model comprising energy consumption, GDP, and exports has the highest accuracy for medium term prediction. Meanwhile, ANNs5 model consisting of energy consumption and population shows the best accuracy for the long term prediction. Overall, it may conclude that exports and population are two essential variables to predict Taiwan’s energy consumption for the short, medium, medium-long, and long term periods. The results support the assumption that parsimonious set of variables incorporated in research models may not sacrifice prediction accuracy. This concludes the contributions of this study.