Stowage planning in maritime container transportation

We consider a stowage-planning problem of arranging containers on a container ship in the maritime transportation system. Since containers are accessible only from the top of the stack, temporary unloading and reloading of containers, called shifting, is unavoidable if a container required to be unloaded at the current port is stacked under containers to be unloaded at later ports on the route of the ship. The objective of the stowage planning problem is to minimize the time required for shifting and crane movements on a tour of a container ship while maintaining the stability of the ship. For the problem, we develop a heuristic solution method in which the problem is divided into two subproblems, one for assigning container groups into the holds and one for determining a loading pattern of containers assigned to each hold. The former subproblem is solved by a greedy heuristic based on the transportation simplex method, while the latter is solved by a tree search method. These two subproblems are solved iteratively using information obtained from solutions of each other. To see the performance of the suggested algorithm, computational tests are performed on problem instances generated based on information obtained from an ocean container liner. Results show that the suggested algorithm works better than existing algorithms.     

A multi-methodological approach to the development of a regional solid waste management system

The management of solid waste at regional level has received considerable attention over the last years. Increased consumption levels are causing an exacerbation of the problem, whereas the sensitivity of the public over environmental issues makes its solution harder. Although the main difficulties in resolving the different occurrences of the problem belong to the realm of policy making, so far the employment of operational research and systems methods seems to adopt a purely technocratic stance, concentrating on the content and understating the solution process. In the different formulations of the problem as static optimization relating to the economics of the location of the treatment facilities and the methods and routes of waste transportation, the dynamics of the issue and the intervention activities are neglected, whereas cognitive and social perspectives of the solution process are objectified and over-rationalized. This paper aims at demonstrating how the solid waste management (SWM) problem and its solution process can be addressed in a more holistic way by adopting a multi-methodological point of view. Towards this end, we present the combined application of soft systems methodology, system dynamics and multi-objective optimization in an action research project for the development of an SWM system for a specific region in Greece.     

A transportation mode selection model for a consolidation warehouse system

Summary This paper presents a transportation mode selection model for a consolidation warehouse system. It determines the transportation mode to be used by each plant or warehouse (point of origin) to ship its order to the company's consolidation point or central warehouse. The model considers the tradeoff between the total cost of transporting items and the maximum time until a complete order has reached the consolidation point. It brings to bare the effect of each possible mode on (1) buyer transportation cost, and (2) related buyer inventory costs. An algorithm is provided to determine the most preferable shipping plan. A prototypical example is presented to illustrate the use of the algorithm.

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Zusammenfassung Es wird ein Liefersystem betrachtet, bei dem die bestellten Waren von verschiedenen Herstellern oder Lagerhäusern über eine gemeinsame Zentrale an den Kunden geliefert werden. Für den Transport der Waren von jedem Hersteller zur Zentrale sind verschiedene Transportarten wählbar, die unterschiedliche Transportkosten und Transportdauern verursachen. Die verschiedenen Transportdauern führen zu unterschiedlichen Lagerhaltungskosten beim Kunden. Es wird ein Modell angegeben, das die mit der gewählten Transportart verbundenen Transportkosten und Lagerhaltungskosten berücksichtigt. Ein Algorithmus zur Auswahl der günstigsten Transportart wird bereitgestellt. An einem kleinen Beispiel wird der Algorithmus erläutert.

     

A mass transportation approach for Sobolev inequalities in variable exponent spaces

In this paper we provide a proof of the Sobolev–Poincaré inequality for variable exponent spaces by means of mass transportation methods, in the spirit of Cordero-Erausquin et al. (Adv Math 182(2):307–332, 2004). The importance of this approach is that the method is flexible enough to deal with different inequalities. As an application, we also deduce the Sobolev-trace inequality improving the result of Fan (J Math Anal Appl 339(2):1395–1412, 2008) by obtaining an explicit dependence of the exponent in the constant.     

A new index for measuring seasonality: A transportation cost approach

Seasonal fluctuations characterize many natural and social phenomena. Although the causes and impacts of seasonality are generally well documented in different study contexts, and many methods for isolating the seasonal component have been developed, considerably less attention has been paid to the measurement of the degree of seasonality. After reviewing the main indices used for measuring seasonality in different study contexts, we will propose a new approach in which seasonality is evaluated on the basis of the solution of a transportation problem. By considering the interdisciplinary nature of seasonal phenomena, the topic of measuring seasonality merits attention from a wide variety of perspectives.     

A fuzzy MCDM approach for stock selection

A fuzzy MCDM approach is applied to the stock selection problem, where the proposed approach can deal with qualitative information in addition to quantitative information. A hierarchy of major–sub criteria is then established to reduce the dependence between criteria. The ratings of alternatives versus qualitative sub-criteria and the weights of major- and sub-criteria are assessed in linguistic terms represented by fuzzy numbers. Each sub-criterion is in a benefit, cost, or balanced nature. New standardization methods for fuzzy numbers in the cost and balanced nature are presented. The algorithms of membership functions of the final aggregation are completely developed instead of approximation. The final aggregations in fuzzy numbers are then defuzzified to crisp values in order to rank the performance of alternatives. Moreover, the ratio of market price to performance (PP) is suggested to filter the over/under-pricing of alternatives. A set of buying/selling strategies are recommended according to the performance and PP. An empirical example then demonstrates the processing of the proposed approach.     

A new approach for solving fully intuitionistic fuzzy transportation problems

In this paper, a well-known network-structured problem called the transportation problem (TP) is considered in an uncertain environment. The transportation costs, supply and demand are represented by trapezoidal intuitionistic fuzzy numbers (TrIFNs) which are the more generalized form of trapezoidal fuzzy numbers involving a degree of acceptance and a degree of rejection. We formulate the intuitionistic fuzzy TP (IFTP) and propose a solution approach to solve the problem. The IFTP is converted into a deterministic linear programming (LP) problem, which is solved using standard LP algorithms. The main contributions of this paper are fivefold: (1) we convert the formulated IFTP into a deterministic classical LP problem based on ordering of TrIFNs using accuracy function; (2) in contrast to most existing approaches, which provide a crisp solution, we propose a new approach that provides an intuitionistic fuzzy optimal solution; (3) in contrast to existing methods that include negative parts in the obtained intuitionistic fuzzy optimal solution and intuitionistic fuzzy optimal cost, we propose a new method that provides non-negative intuitionistic fuzzy optimal solution and optimal cost; (4) we discuss about the advantages of the proposed method over the existing methods for solving IFTPs; (5) we demonstrate the feasibility and richness of the obtained solutions in the context of two application examples.     

A fuzzy approach to the transportation problem

The transportation problem with fuzzy supply values of the deliverers and with fuzzy demand values of the receivers is analysed. For the solution of the problem the technique of parametric programming is used. This makes it possible to obtain not only the maximizing solution (according to the Bellman-Zadeh criterion) but also other alternatives close to the optimal solution.     

A locally linear neuro-fuzzy model for supplier selection in cosmetics industry

Supplier selection and evaluation is a complicated and disputed issue in supply chain network management, by virtue of the variety of intellectual property of the suppliers, the several variables involved in supply demand relationship, the complex interactions and the inadequate information of suppliers. The recent literature confirms that neural networks achieve better performance than conventional methods in this area. Hence, in this paper, an effective artificial intelligence (AI) approach is presented to improve the decision making for a supply chain which is successfully utilized for long-term prediction of the performance data in cosmetics industry. A computationally efficient model known as locally linear neuro-fuzzy (LLNF) is introduced to predict the performance rating of suppliers. The proposed model is trained by a locally linear model tree (LOLIMOT) learning algorithm. To demonstrate the performance of the proposed model, three intelligent techniques, multi-layer perceptron (MLP) neural network, radial basis function (RBF) neural network and least square-support vector machine (LS-SVM) are considered. Their results are compared by using an available dataset in cosmetics industry. The computational results show that the presented model performs better than three foregoing techniques.     

A QFD-based fuzzy MCDM approach for supplier selection

Supplier selection is a highly important multi-criteria group decision making problem, which requires a trade-off between multiple criteria exhibiting vagueness and imprecision with the involvement of a group of experts. In this paper, a fuzzy multi-criteria group decision making approach that makes use of the quality function deployment (QFD) concept is developed for supplier selection process. The proposed methodology initially identifies the features that the purchased product should possess in order to satisfy the company’s needs, and then it seeks to establish the relevant supplier assessment criteria. Moreover, the proposed algorithm enables to consider the impacts of inner dependence among supplier assessment criteria. The upper and the lower bounds of the weights of supplier assessment criteria and ratings of suppliers are computed by using the fuzzy weighted average (FWA) method. The FWA method allows for the fusion of imprecise and subjective information expressed as linguistic variables or fuzzy numbers. The method produces less imprecise and more realistic overall desirability levels, and thus it rectifies the problem of loss of information. A fuzzy number ranking method that is based on area measurement is used to obtain the final ranking of suppliers. The computational procedure of the proposed framework is illustrated through a supplier selection problem reported in an earlier study.     

A diversified AHP-tree approach for multiple-criteria supplier selection

Computational Management Science - A decision maker usually holds various viewpoints regarding the priorities of criteria, which complicates the decision making process. To overcome this concern,...     

A mass transportation approach to quantitative isoperimetric inequalities

A sharp quantitative version of the anisotropic isoperimetric inequality is established, corresponding to a stability estimate for the Wulff shape of a given surface tension energy. This is achieved by exploiting mass transportation theory, especially Gromov’s proof of the isoperimetric inequality and the Brenier-McCann Theorem. A sharp quantitative version of the Brunn-Minkowski inequality for convex sets is proved as a corollary.     

A mathematical programming model for optimal service selection in the airline industry

Airlines, offering tour plans, have to select a few gateways (airports) to which the air tickets for tour plans are issued. A number of alternate gateways are available for different tour plans, and the selection of gateways is influenced by the perceived preferences of tourists for these and competing plans. In this paper, using the ordinal preferences of tourists, we formulate the problem of gateway selection as an integer program. The solution procedure presented for this integer program is computationally attractive as we exploit the special structure of our formulation. The model proposed is general, and can be applied to the simultaneous positioning of several new products or services.     

Integrated scheduling of crane handling and truck transportation in a maritime container terminal

This paper studies the interactions between crane handling and truck transportation in a maritime container terminal by addressing them simultaneously. Yard trucks are shared among different ships, which helps to reduce empty truck trips in the terminal area. The problem is formulated as a constraint programming model and a three-stage algorithm is developed. At the first stage, crane schedules are generated by a heuristic method. At the second stage, the multiple-truck routing problem is solved based on the precedence relations of the transportation tasks derived from the first stage. At the last stage a complete solution is constructed by using a disjunctive graph. The three procedures are linked by an iterative structure, which facilitates the search for a good solution. The computational results indicate that the three-stage algorithm is effective for finding high-quality solutions and can efficiently solve large problems.     

A quantile-based approach to system selection

We propose a quantile-based ranking and selection (R&S) procedure for comparing a finite set of stochastic systems via simulation. Our R&S procedure uses a quantile set of the simulated probability distribution of a performance characteristic of interest that best represents the most appropriate selection criterion as the basis for comparison. Since this quantile set may represent either the downside risk, upside risk, or central tendency of the performance characteristic, the proposed approach is more flexible than the traditional mean-based approach to R&S. We first present a procedure that selects the best system from among K systems, and then we modified that procedure for the case where K − 1 systems are compared against a standard system. We present a set of experiments to highlight the flexibility of the proposed procedures.     

A heuristic approach to the multi-period multi-commodity transportation problem

This paper describes an approach to solving a real-world problem which involves the transportation of multiple types of commodities from a number of sources to a number of destinations in discrete time periods, using a capacitated heterogeneous fleet of vehicles. The preliminary objective is to minimize the total number of discrete periods needed to complete the entire operation. The problem is first formulated as a mixed integer programme and its tractability is then greatly improved by reformulating it through backward decomposition into two separate models and solved iteratively. A heuristic approach harnessing specific features of the second approach is developed for solving large size problems to obtain near-optimal solutions within reasonable time. The design of the heuristic also takes into consideration the secondary objectives of minimizing the total vehicle capacity used and minimizing the total capacity of sources needed to satisfy the demands at the destinations. Computational results are provided for a variety of randomly generated problems as well as problems from the literature. The approach described here may be applied to the multi-period transportation of personnel and goods from multiple starting points to multiple destinations in both military and civilian applications.     

A large deviation approach to some transportation cost inequalities

New transportation cost inequalities are derived by means of elementary large deviation reasonings. Their dual characterization is proved; this provides an extension of a well-known result of S. Bobkov and F. Götze. Their tensorization properties are investigated. Sufficient conditions (and necessary conditions too) for these inequalities are stated in terms of the integrability of the reference measure. Applying these results leads to new deviation results: concentration of measure and deviations of empirical processes.     

A multiple criteria decision-making approach for the selection of stocks

A fundamental principle of modern portfolio theory is that portfolio selectiondecisions are generally made using two criteria, corresponding to the first twomoments of return distributions, namely the expected returnportfolio variance.One criticism over this theory, which has often been addressed both bypractitioners and academics, is that it fails to embody all thedecision-maker's objectives, through the various stages of the decisionprocess. The aim of this paper is to present an alternative methodologicalapproach for modeling one of the most crucial phases of the portfolio managementprocess, the security selection phase. The main characteristic of the proposedapproach is that it fully takes into account the inherent multi-dimensionalnature of the problem, although allowing the decision-maker to incorporate hispreferences in the decision process. The validity of the proposed approach istested through an illustrative application in Athens Stock Exchange. Besides, adetailed categorized bibliography is provided, relative to the application ofthe techniques of multiple criteria decision making to the problems and issuesof portfolio management.     

A DC programming approach for feature selection in support vector machines learning

Feature selection consists of choosing a subset of available features that capture the relevant properties of the data. In supervised pattern classification, a good choice of features is fundamental for building compact and accurate classifiers. In this paper, we develop an efficient feature selection method using the zero-norm l ₀ in the context of support vector machines (SVMs). Discontinuity at the origin for l ₀ makes the solution of the corresponding optimization problem difficult to solve. To overcome this drawback, we use a robust DC (difference of convex functions) programming approach which is a general framework for non-convex continuous optimisation. We consider an appropriate continuous approximation to l ₀ such that the resulting problem can be formulated as a DC program. Our DC algorithm (DCA) has a finite convergence and requires solving one linear program at each iteration. Computational experiments on standard datasets including challenging feature-selection problems of the NIPS 2003 feature selection challenge and gene selection for cancer classification show that the proposed method is promising: while it suppresses up to more than 99% of the features, it can provide a good classification. Moreover, the comparative results illustrate the superiority of the proposed approach over standard methods such as classical SVMs and feature selection concave.     

A best-response approach for equilibrium selection in two-player generalized Nash equilibrium problems

ABSTRACT

In this paper, we propose a best-response approach to select an equilibrium in a two-player generalized Nash equilibrium problem. In our model we solve, at each of a finite number of time steps, two independent optimization problems. We prove that convergence of our Jacobi-type method, for the number of time steps going to infinity, implies the selection of the same equilibrium as in a recently introduced continuous equilibrium selection theory. Thus the presented approach is a different motivation for the existing equilibrium selection theory, and it can also be seen as a numerical method. We show convergence of our numerical scheme for some special cases of generalized Nash equilibrium problems with linear constraints and linear or quadratic cost functions.