This paper presents a coordinated planning model of price-dependent demand for a single-manufacturer and a single-retailer. The demand is assumed to be normally distributed, with its mean being price dependent. The manufacturer and retailer coordinate with each other to jointly and simultaneously determine the retail selling price and the retailer order quantity to maximize the joint expected total profit. This model is then compared to a 'returns' policy model where manufacturer buys back unsold items from the retailers. It is shown that the optimal total profit is higher for coordinated planning model than that for the returns policy model, in which the retail price is set by the retailer. A compensation or profit sharing scheme is then suggested and it is shown that the coordinated model with profit sharing yields a 'win-win' situation. Numerical results are presented to illustrate the profit patterns for both linear and nonlinear demand functions. The coordinated planning model, in addition, has a lower optimal price than for a returns policy model, which would result in higher sales, thus expanding the markets for the whole supply chain.

We formulate a mathematical model of remanufacturing system as multi-stage reverse Logistics Network Problem (mrLNP) with minimizing the total costs for reverse logistics shipping cost and inventory holding cost at disassembly centers and processing centers over finite planning horizons. For solving this problem, in the 1st and the 2nd stages, we propose a Genetic Algorithm (GA) with priority-based encoding method combined with a new crossover operator called as Weight Mapping Crossover (WMX). A heuristic approach is applied in the 3rd stage where parts are transported from some processing centers to one manufacturer. Computer simulations show the effectiveness and efficiency of our approach. In numerical experiments, the results of the proposed method are better than pnGA (Prufer number-based GA).

We consider facility layout problems, where mn facility units are assigned into mn cells. These cells are arranged into a rectangular pattern with m rows and n columns. In order to solve this cell type facility layout problem, many approximation algorithms with improved local search methods were studied because it was quite difficult to find exact optimum of such problem in case of large size problem. In this paper, new algorithms based on Simulated Annealing (SA) method with two neighborhood generation methods are proposed. The new neighborhood generation method adopts the exchanging operation of facility units in accordance with adjacent preference. For evaluating the performance of the neighborhood generation method, three algorithms, previous SA algorithm with random 2-opt neighborhood generation method, the SA-based algorithm with the new neighborhood generation method (SA1) and the SA-based algorithm with probabilistic selection of random 2-opt and the new neighborhood generation method (SA2), are developed and compared by experiment of solving same example problem. In case of numeric examples with problem type 1 (the optimum layout is given), SA1 algorithm could find excellent layout than other algorithms. However, in case of problem type 2 (random-prepared and optimum-unknown problem), SA2 was excellent more than other algorithms.

We present two local-search based metaheuristics for the multi-source capacitated facility location problem. In such a problem, each customer's demand can be supplied by one or more facilities. The problem is NP-hard and the number of locations in the optimal solution is unknown. To keep the search process effective, the proposed methods adopt the following features: (1) a multi-exchange neighborhood structure, (2) a tabu list that keeps track of recently visited solutions, and (3) a multi-start to enhance the diversified search paths. The transportation simplex method is applied in an efficient manner to obtain the optimal solutions to neighbors of the current solution under the algorithm framework. Two in-and-out selection rules are also proposed in the algorithms with the purpose of finding promising solutions in a short computational time. Our computational results for some of the benchmark instances, as well as some instances generated using a method in the literature, have demonstrated the effectiveness of this approach.

Patient safety has become a growing concern in health care. The U.S. Institute of Medicine (IOM) report "To Err Is Human: Building a Safer Health System" in 1999 included estimations that medical error is the eighth leading cause of death in the United States and results in up to 100,000 deaths annually. However, many adverse events and errors occur in surgical practice. Within all kinds of surgical adverse events, wrong-side/wrong-site, wrong-procedure, and wrong-patient adverse events are the most devastating, unacceptable, and often result in litigation. Much literature claims that systems must be put in place to render it essentially impossible or at least extremely difficult for human error to cause harm to patients. Hence, this research aims to develop a prototype system based on active RFID that detects and prevents errors in the OR. To fully comprehend the operating room (OR) process, multiple rounds of on site discussions were conducted. IDEF0 models were subsequently constructed for identifying the opportunity of improvement and performing before-after analysis. Based on the analysis, the architecture of the proposed RFID-based OR system was developed. An on-site survey conducted subsequently for better understanding the hardware requirement will then be illustrated. Finally, an RFID-enhanced system based on both the proposed architecture and test results was developed for gaining better control and improving the safety level of the surgical operations.

We define product line (or mix) selection problem as selecting a subset of potential product variants that can simultaneously minimize product proliferation and maintain market coverage. Selecting the most efficient product mix is a complex problem, which requires analyses of multiple criteria. This paper proposes a method based on Data Envelopment Analysis (DEA) for product line selection. Data Envelopment Analysis (DEA) is a linear programming based technique commonly used for measuring the relative performance of a group of decision making units with multiple inputs and outputs. Although DEA has been proved to be an effective evaluation tool in many fields, it has not been applied to solve the product line selection problem. In this study, we construct a five-step method that systematically adopts DEA to solve a product line selection problem. We then apply the proposed method to an existing line of staplers to provide quantitative evidence for managers to generate desirable decisions to maximize the company profits while also fulfilling market demands.

The existence of Internet revolutionized the computer and communications world. With the rising demand for accessing the Internet, the mobile technology has incorporated the use of Internet in mobile phones. Wireless Application Protocol (WAP) has combined two of the widest utilized technology today: mobile phones and Internet. This study aims to assess the existing WAP pages offered by the top service providers in the Philippines through usability testing experiments. The paper also aims to identify existing problems in WAP interface by focusing on the errors committed by the users. From the usability study, it was found out that common usability problems are wrong selection of links, unclear grouping of categories, wrong feedback, and redundant links. The type of service provider used is significant in determining the performance of users while experience in accessing WAP is insignificant.

This study proposes a new framework for designing disassembly methods. In recent years, environmental problems have become global issues. Recycling of used products or resources is recognized as a matter of significance since it may help reduce the risk of exhausting natural resources. Considering possible exhaustion of limited natural resources in the near future, reuse of products would gain more environmental significance. As yet, it relies hugely on manual disassembly, which labor cost places burden on the total recycling cost. The purpose of this study is to propose a methodology designing for manual disassembly works, and a creation method of a jig. By focusing on parts' connection and attachment relationship, parts are categorized in 5 categories (parent part, joint key part, attaching key part, child part, and independent part) according to the features that parts possess, and 3 kinds of connection relationships (parent part-joint key part connection, parent part-independent part connection and child part-child part connection) are clarified. Connection relationship and attachment relationship charts have also been created, and utilizing them, disassembly orders are settled, and a disassembly jig is devised. The proposed methodology is also applied to a real product and its work time is improved 42% form 31 to 13 seconds.