This paper considers solving a multi-objective optimization problem with sup-T equation constraints. A set covering-based technique for order of preference by similarity to the ideal solution is proposed for solving such a problem. It is shown that a compromise solution of the sup-T equation constrained multi-objective optimization problem can be obtained by solving an associated set covering problem. A surrogate heuristic is then applied to solve the resulting optimization problem. Numerical experiments on solving randomly generated multi-objective optimization problems with sup-T equation constraints are included. Our computational results confirm the efficiency of the proposed method and show its potential for solving large scale sup-T equation constrained multi-objective optimization problems.

In this paper, we develop a unique time-varying forecasting model for dynamic demand of medical resources based on a susceptible-exposed-infected-recovered (SEIR) influenza diffusion model. In this forecasting mechanism, medical resources allocated in the early period will take effect in subduing the spread of influenza and thus impact the demand in the later period. We adopt a discrete time-space network to describe the medical resources allocation process following a hypothetical influenza outbreak in a region. The entire medical resources allocation process is constructed as a multi-stage integer programming problem. At each stage, we solve a cost minimization sub-problem subject to the time-varying demand. The corresponding optimal allocation result is then used as an input to the control process of influenza spread, which in turn determines the demand for the next stage. In addition, we present a comparison between the proposed model and an empirical model. Our results could help decision makers prepare for a pandemic, including how to allocate limited resources dynamically.

Collaboration with universities as ‘knowledge factories’ is increasingly perceived to be an effective and viable solution for firms to gain competitive advantage. One of the main challenges firms face in this area is how to select the best university for collaboration. This selection undoubtedly affects some other strategic activities of firms, such as managing and governing the relationship with the selected university and, most importantly, firm performance. As such, the selection becomes an important strategic decision that deserves a great deal of attention. Thus far, no systematic attempt has been made to investigate this significant area of research. The main purpose of this study is to formulate a decision-making model for university selection. Reviewing existing literature of university-industry relationship yields a list of relevant criteria for this problem. The problem is then formulated as a multi-criteria decision-making (MCDM) model, and a fuzzy AHP is used to provide the solution. To illustrate the model, three Dutch universities are ranked based on the importance of the selected criteria.

The Quality Function Deployment (QFD) is a useful and representative methodology to transform customer needs into different level of requirements in a system hierarchy. Simplifications that are based on assumptions are ubiquitous in the QFD, but these underlying assumptions possibly do not hold true, which renders the simplifications unjustified. Additionally, these assumptions are usually not verified within the context of the application domain. This paper identifies and illustrates eight hidden traps in QFD during the process of establishing the requirements, where the assumptions, and therefore, the simplifications made are not reasonable. These traps are implicit in the understanding of customer needs, establishment of system requirements and the flow down of these requirements to lower levels of the system hierarchy. Suggestions are given to help avoiding these hidden traps, thereby eliminating or alleviating their potentially detrimental effects. The intent of the paper is to make readers aware of these traps when applying QFD for the establishment of requirements, so that they may utilize QFD with a better understanding of its limitations and develop higher quality specifications.

We first consider an infinite-buffer single server queue where arrivals occur according to a batch Markovian arrival process(BMAP). The server serves customers in batches of maximum size ‘b’ with a minimum threshold size ‘a’. The service time of each batch follows general distribution independent of each other as well as the arrival process. The proposed analysis is based on the use of matrix-analytic procedure to obtain queue-length distribution at a post-departure epoch. Next we obtain queue-length distributions at various other epochs such as, pre-arrival, arbitrary and pre-service using relations with post-departure epoch. Later we also obtain the system-length distributions at post-departure and arbitrary epochs using queue-length distribution at post-departure epoch. Some important performance measures, like mean queue-lengths and mean waiting times have been obtained. Total expected cost function per unit time is also derived to determine the locally optimal values of a and b. Secondly, we perform similar analysis for the corresponding infinite-buffer single server queue where arrivals occur according to a BMAP and service process in this case follows a non-renewal one, namely, Markovian service process (MSP).

We in this paper examine warranty strategy in a two-stage supply chain consisting of a manufacturer and two competing retailers. The manufacturer produces two substitute products and markets them through the two retailers to a group of consumers, respectively. For each type of products, the manufacturer’s base warranty and a retailer’s extended warranty are bundled with the product. We use game theoretic models to explore the interactions between the two types of warranties and the competition between the retailers. For this purpose, two scenarios are considered: no retailer and both the two retailers providing the extended warranties, respectively. In each scenario, the manufacturer’s base warranties are assumed to be offered. Our results show that when the retailers offer their extended warranties, the manufacturer has no incentive to offer the base warranties; otherwise, the manufacturer has to provide the base warranties. The competition between retailers in terms of the product substitutability has no impact on warranty decisions, but affects all players’ profits in the supply chain. The manufacturer can provide a longer warranty length and higher customer welfare to a customer than the retailers do, if it is more efficient than the retailers in warranty cost-efficiency, and vice versa.