Uso de un algoritmo Stackelberg-Evolutivo para resolver el problema de fijación de cuotas en una red de transporte

El problema de fijación de cuotas en una red de transporte de bienes múltiples TOP (por sus siglas en inglés, Toll Optimization Problem) se modela como una problema binivel en el cual el líder busca determinar un conjunto de tarifas que se asignan a determinados arcos de dicha red y el seguidor debe elegir por cuáles arcos transportar los bienes, sabiendo que debe pagar las cuotas establecidas por el líder. El siguiente trabajo presenta un algoritmo Stackelberg-Evolutivo para resolver el TOP que estudia la interacción entre el líder y el seguidor como un juego de Stackelberg; asimismo, explota los principios de la computación evolutiva, en la cual se realizan cambios aleatorios entre los individuos de una población de soluciones factibles del problema, seleccionando individuos que contribuyen en mayor medida a mejorar la utilidad de los agentes del juego de Stackelberg. Dicha selección permite que en cada iteración las mejores soluciones tengan mayor probabilidad de sobrevivir, permitiendo que las utilidades del líder y del seguidor vayan mejorando su calidad

A GRASP-Tabu Heuristic Approach to Territory Design for Pickup and Delivery Operations for Large-Scale Instances

Weaddressalogisticsdistrictingproblemfacedbyaparcelcompanywhoseoperationsconsistofpickingupanddeliveringpackages overaserviceregion.Thedistrictingprocessaimstofindapartitionoftheserviceregionintodeliveryandcollectionzonesthat may be served by a single vehicle that departs from a central depot. Criteria to be optimized are to balance workload content among the districts and to create districts of compact shape. A solution approach based on a hybrid procedure that combines elements of GRASP and Tabu Search (TS) is proposed to solve large-scale instances. Numerical experimentation is performed consideringdifferentinstancesizesandtypes.Resultsshowthattheproposedsolutionapproachisabletosolvelarge-scaleinstances inreasonablecomputationaltimeswithgoodqualityofthesolutionsobtained.Todeterminethequalityofthesolutions,resultsare comparedwithCPLEXsolutionsandwiththecurrentrealsolutiontohighlightthebenefitsoftheproposedapproach.Conclusions andrecommendationsforfurtherresearchareprovided

Analyzing the Performance of a Hybrid Heuristic for Solving a Bilevel Location Problem under Different Approaches to Tackle the Lower Level

The problem addressed here is a combinatorial bilevel programming problem called the uncapacitated facility location problem with customer’s preferences. A hybrid algorithm is developed for solving a battery of benchmark instances. The algorithm hybridizes an evolutionary algorithm with path relinking; the latter procedure is added into the crossover phase for exploring the trajectory between both parents. The proposed algorithm outperforms the evolutionary algorithm already existing in the literature. Results show that including a more sophisticated procedure for improving the population through the generations accelerates the convergence of the algorithm. In order to support the latter statement, a reduction of around the half of the computational time is obtained by using the hybrid algorithm. Moreover, due to the nature of bilevel problems, if feasible solutions are desired, then the lower level must be solved for each change in the upper level’s current solution. A study for illustrating the impact in the algorithm’s performance when solving the lower level through three different exact or heuristic approaches is made

Analyzing the Performance of a Hybrid Heuristic for Solving a Bilevel Location Problem under Different Approaches to Tackle the Lower Level

The problem addressed here is a combinatorial bilevel programming problem called the uncapacitated facility location problem with customer’s preferences. A hybrid algorithm is developed for solving a battery of benchmark instances. The algorithm hybridizes an evolutionary algorithm with path relinking; the latter procedure is added into the crossover phase for exploring the trajectory between both parents. The proposed algorithm outperforms the evolutionary algorithm already existing in the literature. Results show that including a more sophisticated procedure for improving the population through the generations accelerates the convergence of the algorithm. In order to support the latter statement, a reduction of around the half of the computational time is obtained by using the hybrid algorithm. Moreover, due to the nature of bilevel problems, if feasible solutions are desired, then the lower level must be solved for each change in the upper level’s current solution. A study for illustrating the impact in the algorithm’s performance when solving the lower level through three different exact or heuristic approaches is made

Bilevel programming and applications

A great amount of new applied problems in the area of energy networks has recently arisen that can be efficiently solved only as mixed-integer bilevel programs. Among them are the natural gas cash-out problem, the deregulated electricity market equilibrium problem, biofuel problems, a problem of designing coupled energy carrier networks, and so forth, if we mention only part of such applications. Bilevel models to describe migration processes are also in the list of the most popular new themes of bilevel programming, as well as allocation, information protection, and cybersecurity problems. This survey provides a comprehensive review of some of the above-mentioned new areas including both theoretical and applied results

A GRASP-Tabu Heuristic Approach to Territory Design for Pickup and Delivery Operations for Large-Scale Instances

We address a logistics districting problem faced by a parcel company whose operations consist of picking up and delivering packages over a service region. The districting process aims to find a partition of the service region into delivery and collection zones that may be served by a single vehicle that departs from a central depot. Criteria to be optimized are to balance workload content among the districts and to create districts of compact shape. A solution approach based on a hybrid procedure that combines elements of GRASP and Tabu Search (TS) is proposed to solve large-scale instances. Numerical experimentation is performed considering different instance sizes and types. Results show that the proposed solution approach is able to solve large-scale instances in reasonable computational times with good quality of the solutions obtained. To determine the quality of the solutions, results are compared with CPLEX solutions and with the current real solution to highlight the benefits of the proposed approach. Conclusions and recommendations for further research are provided

A market regulation bilevel problem: a case study of the Mexican petrochemical industry

International audienceIn this paper, a bilevel programming model is proposed to study a problem of market regulation through government intervention. One of the main characteristics of the problem herein analyzed is that the government monopolizes the raw material in one industry, and competes in another industry with private firms for the production of commodities. Under this scheme, the government controls a state-owned firm to balance the market; that is, to minimize the difference between the produced and demanded commodities. On the other hand, a regulatory organism that coordinates private firms aims to maximize the total profit by deciding the amount of raw material bought from the state-owned firm. Two equivalent single-level reformulations are proposed to solve the problem. The first reformulation is based on the strong duality condition of the lower level and results in a continuous non-linear model. The second reformulation resorts to the complementarity slackness optimality constraints yielding a mixed-integer linear model. Additionally, three heuristic algorithms are designed to obtain good-quality solutions with low computational effort. In this problem, the feasible region of the dual problem associated to the follower is independent from the leader's decision. Therefore, the proposed heuristics exploit this particular characteristic of the bilevel model. Moreover, the third heuristic hybridizes the other two algorithms to enhance its performance. Extensive computational experimentation is carried out to measure the efficiency of the proposed solution methodologies. A case study based on the Mexican petrochemical industry is presented. Additional instances generated from the case study are considered to validate the robustness of the proposed heuristic algorithms. Numerical results indicate that the hybrid algorithm outperforms the other two heuristics. However, all of them demonstrate to be good alternatives for solving the problem. Additionally, optimal solutions of all the instances are obtained by using good quality solutions (given by the hybrid algorithm) as initial solutions when solving the second reformulation via a general purpose solver

Memorias del Primer Congreso Ecuatoriano de Antropología. Volumen II

Este encuentro permitió visualizar los campos fundamentales en los que la antropología ecuatoriana ha incursionado y ha aportado como ciencia social. Se organizaron diez simposios que, de alguna manera, fueron un reflejo de las principales áreas de interés. Esa diversidad temática mostró que la antropología, a la vez que seguía preocupada por temáticas con larga trayectoria en el país como la arqueología, los estudios urbanos y rurales o la etnohistoria, también había incursionado en temáticas nuevas como son género, medio ambiente, identidad, entre otras

Marine Biodiversity in the Caribbean: Regional Estimates and Distribution Patterns

This paper provides an analysis of the distribution patterns of marine biodiversity and summarizes the major activities of the Census of Marine Life program in the Caribbean region. The coastal Caribbean region is a large marine ecosystem (LME) characterized by coral reefs, mangroves, and seagrasses, but including other environments, such as sandy beaches and rocky shores. These tropical ecosystems incorporate a high diversity of associated flora and fauna, and the nations that border the Caribbean collectively encompass a major global marine biodiversity hot spot. We analyze the state of knowledge of marine biodiversity based on the geographic distribution of georeferenced species records and regional taxonomic lists. A total of 12,046 marine species are reported in this paper for the Caribbean region. These include representatives from 31 animal phyla, two plant phyla, one group of Chromista, and three groups of Protoctista. Sampling effort has been greatest in shallow, nearshore waters, where there is relatively good coverage of species records; offshore and deep environments have been less studied. Additionally, we found that the currently accepted classification of marine ecoregions of the Caribbean did not apply for the benthic distributions of five relatively well known taxonomic groups. Coastal species richness tends to concentrate along the Antillean arc (Cuba to the southernmost Antilles) and the northern coast of South America (Venezuela – Colombia), while no pattern can be observed in the deep sea with the available data. Several factors make it impossible to determine the extent to which these distribution patterns accurately reflect the true situation for marine biodiversity in general: (1) highly localized concentrations of collecting effort and a lack of collecting in many areas and ecosystems, (2) high variability among collecting methods, (3) limited taxonomic expertise for many groups, and (4) differing levels of activity in the study of different taxa

Uso de un algoritmo Stackelberg-Evolutivo para resolver el problema de fijación de cuotas en una red de transporte

El problema de fijación de cuotas en una red de transporte de bienes múltiples TOP (por sus siglas en inglés, Toll Optimization Problem) se modela como una problema binivel en el cual el líder busca determinar un conjunto de tarifas que se asignan a determinados arcos de dicha red y el seguidor debe elegir por cuáles arcos transportar los bienes, sabiendo que debe pagar las cuotas establecidas por el líder. El siguiente trabajo presenta un algoritmo Stackelberg-Evolutivo para resolver el TOP que estudia la interacción entre el líder y el seguidor como un juego de Stackelberg; asimismo, explota los principios de la computación evolutiva, en la cual se realizan cambios aleatorios entre los individuos de una población de soluciones factibles del problema, seleccionando individuos que contribuyen en mayor medida a mejorar la utilidad de los agentes del juego de Stackelberg. Dicha selección permite que en cada iteración las mejores soluciones tengan mayor probabilidad de sobrevivir, permitiendo que las utilidades del líder y del seguidor vayan mejorando su calidad