This paper provides an efficient and useful approach for demand estimation and assortment planning of cell phone cards in wireless communication industry. We use maximum likelihood estimation to estimate the primary demand and substitution probability of each cell phone card based on historical sales data. This estimation model is nonlinear, so we transform it to a mixed integer linear programming model by logarithmic transformations and piecewise linear approximation. On the basis of the estimation results, we can make assortment planning. Considering the resource of cell phone cards is limited, we jointly optimize the assortment and quantity planning of cell phone cards. In numerical study, we apply our approach to a large mobile service provider in China and find our approach can increase the revenue of this mobile service provider by 23.69%. Sensitivity analysis shows the mobile service provider should provide more assortments to increase revenue when the types of cell phone cards that can be assigned to each store are limited.

Although many theories regarding the implementation of knowledge management (KM) in organizations have been proposed and studied, most applications tend to stand alone without incorporating the business processes. Different categories of knowledge provide different benefits and how to integrate various categories of KM into a hybrid approach as an effective KM manner remains strategically important, and yet is still understudied. Therefore, in this paper a hybrid model that integrates principal KM applications for new service development (NSD) and the measurement of the resulting financial benefits have been developed. The proposed KM model incorporates newsgroups, knowledge forums, knowledge asset management and knowledge application processes as a hybrid means for sharing organizational knowledge along two axes, explicit vs. implicit and individual vs. collective. One of the largest management consulting companies in Taiwan, China, whose process model of NSD was standing alone with KM applications, was selected for the case study. A set of hybrid KM processes was developed to implement the proposed KM model, and it illustrates an application with greater financial benefits for integrating hybrid KM practices into the business process. Based on knowledge value added (KVA) validation, the proposed KM model provides a new operating system for sharing NSD knowledge within an organization. Through the case study by measuring the achieved financial results, the proposed KM model is found to provide an exclusive hybrid platform with an empirical process model to address innovative approaches and practical values of KM within an organization.

Call centers have grown world-wide during the past decade. One of the most important aspects considered by call center managers is the optimization of its operators, which implies covering the highly variable demand and finding an efficient way to assign people to certain shifts in order to achieve a desirable service level and abandonment rate. Another challenge is determining which system setup is appropriate for the specific call center. Should we have a single-skill call center or multi-skill call center? If we do have the latter, how many multi-skill agents should we have on staff? In this case study, we generate and analyze discrete-event systems simulation-optimization models to test the behavior of a real-world call center under the actual configuration and under different levels of cross-training. The model results help call center managers by: 1) determining the optimal number of operators needed for different staff configurations in order to achieve the targets for service level and abandonment; 2) providing information about the trade-off between the key measurements in the call center; and 3) providing useful information about the number of operators needed and used for each hour of operation to estimate the number of four-hour shifts required to achieve the performance targets. Our experimental findings from this case study suggest that a bi-skill call center is economically better in the long-run compared to a full-skill or single-skill call center. This case study augments the call center body of knowledge by providing additional managerial insights for the operations management community.

This paper deals with the modeling, analysis and optimization of a specific kind of real industrial problems. This class of problems is known in the literature as Cyclic Hoist Scheduling Problem (CHSP). In such class of problems, several jobs have to flow through a production line according to an ordered bath sequence. The CHSPs appear in the manufacturing facilities to achieve a mass production and to search a repetitive sequence of moves for the hoist. In this paper, we develop P-Temporal Petri Net models to represent the behavior and validate certain qualitative properties of the basic production line. Afterward, complex configurations of the production line are modeled and their properties such as reachability of desired functioning (cyclic operation), deadlock-free, resource sharing and management are checked and validated. A mathematical analysis and a simulation study of all proposed Petri net models are carried out using mathematical fundaments of Petri nets and a Visual Object Net ++ tool. The second part of the paper deals with the development of a mixed integer linear programming models to optimize processing of each line configuration. Optimal manufacturing plans of the studied system with cyclic processing sequences are defined and the feasibility of optimal cyclic scheduling of each configuration is proved.

Many ocean transportation hub systems consist of two container ports that share the container handling business in the area. The container flow passing through a port is the main measurement of the port’s competitiveness. In this paper we adopt a Hotelling model to study the container port competition in a so-called “dual gateway-port system”. The system contains two ports and two terminals, one belonging to each port. The two governments in which the two ports are located compete on cargo fees and the two terminals determine service price and service quality. We study two models with different levels of competition between the terminals. In the first model, the two terminals are owned by two different operators and in the second model, the two terminals are centralized under one operator. The second model exists in practice but is not well studied in the literature. We derive the cargo fee, terminal service price, and service quality equilibria for these two models. We investigate the competition outcome sensitivity with a numerical study. The numerical results reveal that governments prefer terminals to compete with each other. If the terminals do not have competitive advantages in their service quality, then terminal centralization brings more profits to the terminal operator than the competition case.

In an integrated iron and steel plant with a cogeneration system, recycled energy is continuously transported into the cogeneration system and the electricity is continuously generated, and both of them could not be stored for a long time. Moreover, the generation and consumption of electricity is irregular, which may bring about more unexpected imbalances. Therefore, it is a crucial issue to schedule the entire energy system by optimizing the operation of energy utilization, which includes the raw energy in the production system, the generation electricity in the cogeneration system and the recycled energy in these two systems. In this paper, an improved Linear Programming model for energy optimization in the integrated iron and steel plant with a cogeneration system is established. The improved model focuses on controlling the whole energy flow and scheduling the whole energy consumption in the entire energy system between the production system and cogeneration system through optimizing all kinds of energy distribution and utilization in an integrated iron and steel plant with a cogeneration system. Case study shows that the improved model offers the optimal operation conditions at the higher energy utilization, lower energy cost and lower pollution emissions.