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The awareness of environmental protection/conservation and sustainable development has increased in the last two decades. In the competitive thin film transistor liquid crystal display (TFT-LCD) industry, green supplier evaluation involves environmental criteria in the traditional evaluation process and emphasises that TFT-LCD manufacturers should improve the performance of their suppliers with limited resources. The purpose of this study is to develop a hybrid multiple criteria decision-making with preference ranking organisation method for enrichment evaluations to evaluate and assist polariser suppliers for improving the performance of green suppliers in the TFT-LCD industry to achieve the aspiration level. Based on supplier audit forms, the proposed methods are as follows: to develop a decision framework by an influential network relation map (INRM); to obtain the influential weights of the criteria; to involve the concept of aspiration levels in the preference function; and to evaluate and reduce the...

This paper focuses on sensitivity analysis of the degenerate transportation problem (DTP) when perturbation occurs on one cost coefficient. The conventional Type I sensitivity analysis of the transportation problem (TP) determines the perturbation ranges for the invariant optimal basis. Due to different degenerate optimal basic solutions yielding different Type I ranges, the Type I range is misleading for the DTP. Type II sensitivity analysis, which determines the perturbation ranges for the invariant shipping pattern, is more practical for the DTP. However, it is too tedious to obtain Type II ranges by enumerating all optimal basic solutions and all primal optimal basic solutions while getting the union of each corresponding Type I ranges. Here, we propose two labeling algorithms to determine the Type II ranges of the cost coefficient. Besides, three lemmas are provided for obtaining the upper bound or lower bound of the Type II ranges of the cost coefficient directly under specific conditions of the DTP. A numerical example is given to demonstrate the procedure of the proposed labeling algorithms and computational results have been provided.

End-stage renal disease (ESRD) has been a widespread disease in many countries, especially in Taiwan. According to the statistics of United States Renal Data System, Taiwan had high incidence rate of ESRD and the highest prevalence rate of ESRD in 2008. To prevent further increase in both incidence and prevalence of ESRD, the government has proposed many incentive programs to stimulate better medical quality. In this study, we develop a continuous-time Markov chain model to estimate the patients’ life expectancy and their individual disease progression of ESRD. Moreover, we construct a mathematical model for allocating resources to incentive programs to maximize patients’ life expectancy under the limited funds. The results obtained can help decision-makers realize the impact of patients’ attributes on their life expectancies before and after the implementation of incentive programs, and provide suggestions to the government for allocating resources to achieve optimal patients’ effectiveness.

This study considers pricing policies in a supply chain with one manufacturer, who sells a product to an independent retailer and directly to consumers through an Internet channel. In addition to the manufacturer’s product, the retailer sells a substitute product produced by another manufacturer. Given the wholesale prices of the two substitute products, the manufacturer decides the retail price of the Internet channel, and the retailer decides the retail prices of the two substitute products. Both the manufacturer and the retailer choose their own decision variables to maximize their respective profits. This work formulates the price competition, using the settings of Nash and Stackelberg games, and derives the corresponding existence and uniqueness conditions for equilibrium solutions. A sensitivity analysis of an equilibrium solution is then conducted for the model parameters, and the profits are compared for two game settings. The findings show that improving brand loyalty is profitable for both of the manufacturer and retailer, and that an increased service value may alleviate the threat of the Internet channel for the retailer and increase the manufacturer’s profit. The study also derives some conditions under which the manufacturer and the retailer mutually prefer the Stackelberg game. Based on these results, this study proposes an appropriate cooperation strategy for the manufacturer and retailer.

This paper concentrates on sensitivity analysis of the fuzzy assignment problem (FAP). Since most real environments are uncertain, the FAP is more realistic than the assignment problem in application. Owing to the high degeneracy of the FAP, as that of the assignment problem, traditional sensitivity analysis, called Type I sensitivity analysis, which determines the range in which the current optimal basis remains optimal, is impractical. Hence, we attempt to perform other two types of advanced sensitivity analysis, called Type II and Type III sensitivity analysis, to overcome this problem. A labeling algorithm is then presented, where Type II sensitivity analysis is to determine the range of perturbation to keep the current optimal assignment remaining optimal, and Type III sensitivity analysis is to determine the range for which the rate of change of optimal value function remains unchanged. The procedure of the labeling algorithm is divided into two parts: one is when the unassigned cell is perturbed, and the other is when the assigned cell is perturbed. An example is presented to demonstrate that the labeling algorithm is a useful tool for determining the Type II and Type III sensitivity analysis of the FAP.

In this article, equal pricing strategies are studied in a dual channel supply chain where a manufacturer sells to a retailer as well as to consumers through a direct channel according to the assumption that the manufacturer commits setting the same retail price as the traditional channel to reduce the channel’s conflict. The authors first analyze the effect of different pricing strategies on the retail price, wholesale price and profits. The cooperative strategy is also studied to see how it benefits both parties in the dual channel supply chain. Finally, through a numerical example, it is demonstrated that providing convenience of the direct channel is important for the manufacturer and service is a distinctive advantage for the retailer. Furthermore, the paper shows that if the service quality has a significant effect on the direct channel, then the manufacturer tends to abandon commitment of equal pricing strategy.

Radiation therapy is a common and important treatment for some specific tumors in the treatment of cancer. In recent years, there has been a new development in radiation therapy, intensity-modulated radiation therapy (IMRT). IMRT modulates the intensity of the radiation beam to focus a higher radiation dose on the tumor while minimizing radiation exposure to surrounding normal tissues. This study aims to investigate the optimal selection of beam angles. Besides limiting the radiation dose to the tumor and the adjacent organs, we also take the dose distribution into consideration and optimize the beam angles and beam intensity maps simultaneously. Compared with the typical equi-spaced model, our proposed approach can provide optimal beam configuration to help physicians in decision-making.

Open shortest path first (OSPF) is the most widely used intra-domain Internet routing protocol. The OSPF protocol directs the Internet traffic along the shortest paths that are defined by the links weight. Traffic engineering is responsible for improving the network performance, for instance, the objective function that minimizes the maximal link utilization which is usually adopted to avoid the network congestion. This paper formulates the model of OSPF routing, and further evaluates the performance of different approaches. We also propose a heuristic algorithm to solve the routing problems by optimizing OSPF weights. Computational results indicated that the proposed algorithm could lead to good load balancing, and make efficient utilization of network resources.

Information of sensitivity analysis, in a linear programming problem, is usually more important than the optimal solution itself. However, traditional sensitivity analysis, which perturbs exactly one coefficient and then determines the range preserving the optimality of the current optimal base, is impractical for the assignment problem. An optimal basic solution of the assignment problem is inherently degenerate, so it may be that the optimal base has changed but the optimal assignment remains unchanged. Furthermore, elements of a column (or row) in a cost matrix of assignment problem are usually closely related and change simultaneously, not uniquely. This paper focuses on two kinds of sensitivity analyses for the assignment problem. One is to determine the sensitivity range, over which the current optimal assignment or all the optimal assignments remain optimal, while perturbing the elements of one column (or row) in a cost matrix of the assignment problem simultaneously but dependently. The other is to perturb elements of one column (or row) in a cost matrix of the assignment problem simultaneously but independently. Numerical illustrations are presented to demonstrate that the approaches are useful in practice.

This paper considers quality of service in terms of end-to-end delay in planning backup routes for multicast communications. The problem of preplanning backup routes considering both cost minimization and end-to-end delay guarantee for multicast communications in the case a single link failure is investigated. Two delay labels, the limited label and the tolerable label, are defined to evaluate the end-to-end delay requirement. Four heuristic algorithms, including two tree-based algorithms, one subtree-based algorithm, and one link-based algorithm, are proposed to determine the delay-constrained backup routes having the minimum costs. Two procedures to determine a node selection sequence, Random and Minimum-Cost, are used in the tree-based algorithm. Experimental results show that the tree-based algorithm by the Minimum-Cost sequence yields the best performance in cost minimization with guarantee of end-to-end delay.

More and more multimedia applications rely on the ability of networks to provide multicast communications. Network survivability becomes a critical issue in network planning, design, and operation to reduce the impacts of failures in high-speed networks. A rapid and cost-effective restorable network must be planned to maintain network survivability and use network bandwidth effectively. This paper considers the problem of preplanning delay-constrained backup path for multicast networks to minimize the total cost of all the backup paths. Based on the path restoration scheme, a tabu search (TS) algorithm is proposed to find a near optimal solution for the problem under investigation. Diversification and intensification strategies are suggested. The computational experiments are conducted to demonstrate the performance of the proposed TS algorithm. The results show that it offers high-quality solutions within a short amount of time.

This study aims at utilizing the dynamic behavior of artificial neural networks (ANNs) to solve multiobjective programming (MOP) and multilevel programming (MLP) problems. The traditional and non-traditional approaches to the MLP are first classified into five categories. Then, based on the approach proposed by Hopfield and Tank [1], the optimization problem is converted into a system of nonlinear differential equations through the use of an energy function and Lagrange multipliers. Finally, the procedure is extended to MOP and MLP problems. To solve the resulting differential equations, a steepest descent search technique is used. This proposed nontraditional algorithm is efficient for solving complex problems, and is especially useful for implementation on a large-scale VLSI, in which the MOP and MLP problems can be solved on a real time basis. To illustrate the approach, several numerical examples are solved and compared.

In this paper we study the network planning problem of bi-directional self-healing ring (BSHR), which is a network structure providing higher survivability when there is a failure on link or node. Given a network with nodes, links, and demand pairs, our target is to design an optimal network comprising rings, which use only the existing links to satisfy all demands. The objective is to minimize the total amount of equipment (add/drop multiplexer) on nodes, thus reducing the major cost of SHR structure. We propose two integer programming models. For larger networks, we have developed an efficient solution procedure based on its hierarchical network structure. Computational results are given to show that the solution procedure is effective in obtaining an optimal or near-optimal solution.

The awareness of the need for environmental protection is increasing throughout the world. The focuses of green supplier selection are on considering environmental criteria and strengthening the competitiveness of the entire supply chain. The purpose of this study is to develop a green supplier selection procedure for the thin film transistor liquid crystal display (TFT-LCD) industry using polarizer suppliers as an example. First, a decision framework for green supplier selection is developed based on literatures and the supplier audit forms provided by an anonymous flat panel display manufacturer in Taiwan. Then, a hybrid multiple criteria group decision-making (MCGDM) method is proposed based on analytic hierarchy process (AHP), entropy, elimination and choice expressing the reality III (ELECTRE III), and the linear assignment method to assist the manufacturer in choosing among four polarizer suppliers. The final ranking results for green supplier selection and different opinions from each department are provided. An improvement report is suggested to enhance suppliers’ performance. For the evaluation procedure, most managers emphasize the importance of current capability and the capability of research and development. Furthermore, we found that the subsidiary supplier should improve quality control competence immediately to be considered as the potential candidate of primary supplier.

In an asynchronous transfer mode (ATM) network, given the network topology and traffic demands, the establishment of the system of virtual paths (VPs), and the assignment of connections to them so that the network performance is optimized, entails a number of computationally hard subproblems. The optimization problem discussed here focuses on finding a system of VP routes for a given set of VP terminators and VP capacity demands. Although it has been proven that the existing random path algorithm yields the worst case time bound, the solution performance still depends highly on the number of iterations. In this paper, an exact solution procedure and a heuristic method based on a simple tabu search have been developed for optimizing the system of VPs. Computational results show that the proposed tabu search algorithm is effective in obtaining high quality solutions, and the performance of the proposed algorithm is increasingly attractive as the problem size becomes larger.

The efficient set of a multiple objective linear programming problem is usually nonconvex, hence linear optimization over the efficient set problem is classified as a nonlinear optimization problem. This paper presents a modified interior point algorithm for solving linear optimization over the efficient set problems. Using computational experiments, we show that the modified algorithm provides an effective and accurate approach for solving the linear optimization over the efficient set problem.

The travel time models of Automated Storage and Retrieval systems (AS/RS) machines under randomized storage proposed by Chang et al. (IIE Transactions, 27(1), 108–111, 1995), which consider the speed profiles in real-world applications, are extended in this paper. In the present study, travel time models are proposed that consider various travel speeds with known acceleration and deceleration rates. Compact forms of expected travel times under the class-based storage assignment and full-turnover-based storage assignment have been determined. The results show that both the proposed exponential travel time model and the adjusted exponential model perform satisfactorily and could be useful tools for designing an AS/RS in real-world applications.

This paper employs tabu search to solve the network spare capacity planning problem. Our study involves the determination of the necessary spare capacity on each link of a network required to achieve a certain desired level of restoration at minimum cost during network failure. We have developed here a procedure based on tabu search. The computational results show that the proposed tabu search algorithm offers an effective and efficient way for handling this network restoration problem. Scope and purpose Telecommunication network plays a crucial role in modern communication. An ever increasing number of end users are completely relying on telecommunication in their business activities today. The use and integration of computers with telecommunication have created a new information era. In order to provide the much desired broadband services, high capacity transport systems are widely adopted in the transmission network. While these systems offer great economic advantages through multiplexing and sharing of transmission facilities, they also increase the vulnerability of the telecommunication services dependent on them. If a failure occurs on a high speed facility of such a network, all the related services get affected. Network survivability has, therefore, become a major concern in broadband network planning. One of the methods to improve network survivability is to keep redundant or spare capacity for Digital Cross-Connect System (DCS) to restore failed services. However, the problem of spare capacity deployment on the links of a restorable network is NP-hard, implying exponential growth in execution time with network size for an exact solution. In this paper, an algorithm based on tabu search is proposed to find an approximate optimal solution for this problem.

The Tabu search method is currently used in research to solve a range of scheduling problems. The method achieves superior results compared to the other heuristic methods for solving the same problem. In this paper, we compare the solution procedures of the flow shop sequencing problems that have been studied in the literature based on Tabu search. We investigate the algorithms using two heuristic rules to find the starting solution and two kinds of neighborhood structures. The computational results of the different combinations demonstrate some of the desirable characteristics of the Tabu search approach.

The travel-time models of automated storage/retrieval machines, proposed by Chang, Wen and Lin (IIE Transactions, 27 (1), 108-111(1995)), which consider the speed profiles in real world applications, have been extended in this paper to investigate the impact on the rack configuration. The results demonstrate that the optimal rack configuration of the single-command cycle is square-in-time whereas the dual-command cycle may not be. Furthermore, the travel times for both single- and dual-command cycles are quite insensitive to the deviation in the length of the rack configuration.

In this article, equal pricing strategies are studied in a dual channel supply chain where a manufacturer sells to a retailer as well as to consumers through a direct channel according to the assumption that the manufacturer commits setting the same retail price as the traditional channel to reduce the channel’s conflict. The authors first analyze the effect of different pricing strategies on the retail price, wholesale price and profits. The cooperative strategy is also studied to see how it benefits both parties in the dual channel supply chain. Finally, through a numerical example, it is demonstrated that providing convenience of the direct channel is important for the manufacturer and service is a distinctive advantage for the retailer. Furthermore, the paper shows that if the service quality has a significant effect on the direct channel, then the manufacturer tends to abandon commitment of equal pricing strategy.

Multilevel programming is characterized as mathematical programming to solve decentralized planning problems. The models partition control over decision variables among ordered levels within a hierarchical planning structure of which the linear bilevel form is a special case of a multilevel programming problem. In a system with such a hierarchical structure, the high-level decision making situations generally require inclusion of zero-one variables representing ‘yes-no’ decisions. We provide a mixed-integer linear bilevel programming formulation in which zero-one decision variables are controlled by a high-level decision maker and real-value decision variables are controlled by a low-level decision maker. An algorithm based on the short term memory component of Tabu Search, called Simple Tabu Search, is developed to solve the problem, and two supplementary procedures are proposed that provide variations of the algorithm. Computational results disclose that our approach is effective in terms of both solution quality and efficiency.

In this note we propose a travel-time model of automated storage/retrieval (S/R) machines by considering the speed profiles that exist in real-world applications. Compact forms of expected travel-times under randomized storage conditions have been determined for both single and dual command cycles.

A dynamic pricing model in airline seat allocation, where a seller offers two substitutable perishable products in the monopolist market, is proposed in this article. The objective is to maximize the total profit gained from both products. We analyze the problem using a multinomial logit model to describe the customer choice behavior. The exact solution is obtained according to the calculated optimal time thresholds. Sellers can dynamically adjust the price policy in the continuous-time process. We also analyze the efficient price strategy according to the marginal expected revenue function. Furthermore, a numerical example is given to illustrate the procedure and the result is compared with the fixed price policy.