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In the last years, many areas in science, business, and engineering have experienced an enormous growth in the amount of data that they are required to analyze. In many cases, this analysis relies intimately on data visualization and, as a result, graph drawing has emerged as a new field of research. This paper addresses the challenge of drawing hierarchical graphs, which is one of the most widely used drawing standards. We introduce a new mathematical model to automatically represent a graph based on the alignment of long arcs, which we combine with the classic arc crossing minimization objective in hierarchical drawings. We complement our proposal with a heuristic algorithm that can obtain high-quality results in the short computational time required by graph drawing systems. Our algorithm joins two methodologies, tabu search and strategic oscillation (SOS), to perform a fast and effective exploration of the search space. We conduct extensive experimentation that integrates our new mathematical programming formulation and the SOS tabu search that targets large instances. Our statistical analysis confirms the effectiveness of this proposal. [ABSTRACT FROM AUTHOR]

Job shop scheduling problem is very important one in real application of many kind of industries. In the real world applications, there exist many different kinds of disruptions with different sizes. In this situation, beyond the optimality of the final solution, its ability to absorb disruptions is vital, so that the final solution remains feasible in the case of occurring predicted disruptions. In this paper a robust job shop scheduling problem under disruptions is considered. It is intended to generate robust schedules which are able to absorb a predefined range of disruptions. For this reason, two robustness indices are proposed and the related formulas for computing the required buffer times to reach the desired robustness level are proposed. For this purpose, four methods are proposed to solve the variant defined robust job shop scheduling problem, including (1) a mathematical model, (2) a Branch and Bound algorithm, (3) a beam search algorithm, and (4) a meta-heuristic algorithm based on the particle swarm optimization (PSO) method. The first and second methods result in optimum solution. As the size of the problem increases, the required time to find the optimum solutions raises, so that no solutions can be achieved in rational amount of time, e.g. one hour. Therefore, the third and fourth methods are proposed to find good solutions even for large-scale problem in a limited amount of time. Finally, the algorithms are compared using some randomly generated instances. The results show that each algorithm can outperform the others in different conditions. [ABSTRACT FROM AUTHOR]

Abstract: Data envelopment analysis (DEA) has been developed as a method to evaluate efficiency of Decision Making Unit (DMU). In order to analyze DMU in detail, each DEA model is formulated as a mathematical programming problem utilizing the values of inputs and outputs of all DMUs as coefficients. Each DMU is evaluated by a different weight. Then, the efficiency score of each DMU is determined by using an advantageous weight for itself. In general, the efficiency score is obtained by selecting the most advantage weight. In some real cases, seeking the best ranking is sometimes more important than maximizing the efficiency score. In this paper, we propose a model called rank-based measure (RBM) to evaluate DMU from a different standpoint. We suggest a method to obtain a weight which gives the best ranking, and calculates a weight between maximizing the efficiency score and keeping the best ranking. In order to calculate an efficiency score and the best ranking, we repeatedly solve linear programming problems. Moreover, we apply RBM model to the cross efficiency evaluation. Furthermore, a numerical experiment is shown to compare the rankings and scores with traditional evaluations. [Copyright &y& Elsevier]

Abstract: Optimal allocation of emergency resources is a crucial content of emergency management. It is a key step in emergency rescue and assistance. Multiple resources and potential secondary disasters are often neglected in the existing methods, which desperately need to be improved. In this paper, we formulate the emergency resource allocation problem with constraints of multiple resources and possible secondary disasters, and model the multiple resources and multiple emergency response depots problem considering multiple secondary disasters by an integer mathematical programming. For the complexity, a heuristic algorithm is designed to efficiently solve it based on linear programming and network optimization. The algorithm modifies the solutions of the linear programming by setting a priority of preference for each location where the secondary disasters will take place with certain possibilities. The numerical simulation provides evidence for its effectiveness and efficiency. Our method and algorithm can also be implemented in the practical applications with large-scale scenario. [Copyright &y& Elsevier]

Abstract: Similar to traditional brick-and-mortar shops, e-commerce websites also should perform well in terms of various performance criteria in order to win and retain customers. A number of e-commerce performance criteria have been identified in the literature. From the point of view of the manager of an e-commerce website, the relative importance levels customers attribute to these performance criteria are important. In this paper, we propose a new mathematical programming model for estimating the importance levels. The model is based on the Analytic Hierarchy Process and operationalised using goal programming. Application of the model highlights that the criterion “satisfaction with claims” is valued by customers as the most important criterion. This criterion requires coordination with multiple echelons of the supply chain – a clear description by the manufacturer of the product, introducing the correct description in the e-commerce website, processing customer orders accurately, and, picking and dispatching the right product from the warehouse. [Copyright &y& Elsevier]

Abstract: The selection of suppliers and the evaluation of their performance are challenging complex task faced by manufacturing managers in a global market. This is mainly due to three hurdles: (1) various criteria that characterize the supplier performance, (2) risk and uncertainty associated with supplier performance on multiple measures and (3) intangible attributes in cross- countries such as the political, legal, economic, socio-cultural and technological features. The paper develops a stochastic efficiency analysis model to deal with these three hurdles. The model is a new methodological extension to data envelopment analysis (DEA) and applicable to efficiency analysis for entities from different systems with imbedded uncertainty. The application of the proposed model to the international supplier evaluation is the first attempt to model suppler performance from different sub-systems with different environment factors and uncertainty using Stochastic DEA. [Copyright &y& Elsevier]

Abstract: Strategic alliances are widely used in business to obtain the synergy effect and competitive advantage. On the basis of the resource-based view, it can be seen that the valuable resources of firms provide the motivation for entering into strategic alliances. Therefore, the issue of partner selection plays a critical role in the performance of strategic alliances. Although many mathematical programming models have been proposed to deal with the partner selection problems, two main issues such as objective synergies and resource allocations are seems to be ignored. In this paper, a new multiobjective programming model is proposed to determine the optimal partners in the alliance and the corresponding resource allocations. Furthermore, a numerical example is used to demonstrate the proposed method and compared with the conventional method. From the results, it can be concluded that objective synergies and resource allocations play a significant role in the problem of partner selection and should not be ignored in the realistic alliance’s problems. [Copyright &y& Elsevier]