12 research outputs found

    A review on delivery routing problem and its approaches

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    In this paper, a review is conducted specifically in the delivery routing problem, so as to understand its problems and approaches on the current developments and publications. The variants of delivery routing problem were categorized according to the constraints considered in solving the problem. The solution algorithms for the delivery routing problem were classified into hybrid and non-hybrid approaches. A collection of benchmark datasets and real case studies is also presented in relation to the delivery routing problem. The review helps to summarize and record a comprehensive survey on the delivery routing problem. The aims is to organize the variants components of delivery routing problems in a manner that provides a clear view for the readers. New potential research directions resulting from the study is also presented

    A Bio-Inspired Algorithm for Searching Relationships in Social Networks

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    Proceedings of: Third International Conference on Computational Aspects of Social Networks (CASoN).Took place 2011, October,19-21 , in Salamanca (Sapin).The event Web site is http://www.mirlabs.net/cason11/Nowadays the Social Networks are experiencing a growing importance. The reason of this is that they enable the information exchange among people, meeting people in the same field of work or establishing collaborations with other research groups. In order to manage social networks and to find people inside them, they are usually represented as graphs with persons as nodes and relationships between them as edges. Once this is done, establishing contact with anyone involves searching the chain of people to reach him/her, that is, the search of the path inside the graph which joins two nodes. In this paper, a new algorithm based on nature is proposed to realize this search: SoS-ACO (Sense of Smell - Ant Colony Optimization). This algorithm improves the classical ACO algorithm when it is applied in huge graphs.This study was funded through a competitive grant awarded by the Spanish Ministry of Education and Science for the THUBAN Project (TIN2008-02711) and through MA2VICMR consortium (S2009/TIC-1542, http://www.mavir.net), a network of excellence funded by the Madrid Regional Government.Publicad

    Using the ACO algorithm for path searches in social networks

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    The original publication is available at www.springerlink.comOne of the most important types of applications currently being used to share knowledge across the Internet are social networks. In addition to their use in social, professional and organizational spheres, social networks are also frequently utilized by researchers in the social sciences, particularly in anthropology and social psychology. In order to obtain information related to a particular social network, analytical techniques are employed to represent the network as a graph, where each node is a distinct member of the network and each edge is a particular type of relationship between members including, for example, kinship or friendship. This article presents a proposal for the efficien solution to one of the most frequently requested services on social networks; namely, taking different types of relationships into account in order to locate a particular member of the network. The solution is based on a biologically-inspired modificatio of the ant colony optimization algorithm.This study was funded through a competitive grant awarded by the Spanish Ministry of Education and Science for the THUBAN Project (TIN2008-02711) and through MA2VICMR consortium (S2009/TIC-1542, http://www.mavir.net), a network of excellence funded by the Madrid Regional Government.Publicad

    Metaheuristic approach to transportation scheduling in emergency situations

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    This paper compares two metaheuristic approaches in solving a constrained transportation scheduling problem, which can be found in transporting goods in emergency situations. We compared Greedy Search, Parameter-less Evolutionary Search and Ant-Stigmergy Algorithm. The transportation scheduling/allocation problem is NP-hard, and is applicable to different real-life situations with high frequency of loading and unloading operations; like in depots, warehouses and ports. To evaluate the efficiency of the presented approaches, they were tested with four tasks based on realistic data. Each task was evaluated using group and free transportation approach. The experiments proved that all tested algorithms are viable option in solving such scheduling problems, however some performing better than others on some tasks

    Essays on Shipment Consolidation Scheduling and Decision Making in the Context of Flexible Demand

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    This dissertation contains three essays related to shipment consolidation scheduling and decision making in the presence of flexible demand. The first essay is presented in Section 1. This essay introduces a new mathematical model for shipment consolidation scheduling for a two-echelon supply chain. The problem addresses shipment coordination and consolidation decisions that are made by a manufacturer who provides inventory replenishments to multiple downstream distribution centers. Unlike previous studies, the consolidation activities in this problem are not restricted to specific policies such as aggregation of shipments at regular times or consolidating when a predetermined quantity has accumulated. Rather, we consider the construction of a detailed shipment consolidation schedule over a planning horizon. We develop a mixed-integer quadratic optimization model to identify the shipment consolidation schedule that minimizes total cost. A genetic algorithm is developed to handle large problem instances. The other two essays explore the concept of flexible demand. In Section 2, we introduce a new variant of the vehicle routing problem (VRP): the vehicle routing problem with flexible repeat visits (VRP-FRV). This problem considers a set of customers at certain locations with certain maximum inter-visit time requirements. However, they are flexible in their visit times. The VRP-FRV has several real-world applications. One scenario is that of caretakers who provide service to elderly people at home. Each caretaker is assigned a number of elderly people to visit one or more times per day. Elderly people differ in their requirements and the minimum frequency at which they need to be visited every day. The VRP-FRV can also be imagined as a police patrol routing problem where the customers are various locations in the city that require frequent observations. Such locations could include known high-crime areas, high-profile residences, and/or safe houses. We develop a math model to minimize the total number of vehicles needed to cover the customer demands and determine the optimal customer visit schedules and vehicle routes. A heuristic method is developed to handle large problem instances. In the third study, presented in Section 3, we consider a single-item cyclic coordinated order fulfillment problem with batch supplies and flexible demands. The system in this study consists of multiple suppliers who each deliver a single item to a central node from which multiple demanders are then replenished. Importantly, demand is flexible and is a control action that the decision maker applies to optimize the system. The objective is to minimize total system cost subject to several operational constraints. The decisions include the timing and sizes of batches delivered by the suppliers to the central node and the timing and amounts by which demanders are replenished. We develop an integer programing model, provide several theoretical insights related to the model, and solve the math model for different problem sizes

    Penyelesaian Permasalahan Vehicle Routing dengan Objektif Jamak yang Mempertimbangkan Keseimbangan Jarak Rute Kendaraan Menggunakan Metode Hiperheuristik

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    Vehicle Routing Problem (VRP) adalah salah satu permasalahan kombinatorik yang sulit dipecahkan. VRP bertujuan untuk menghasilkan serangkaian rute terpendek dari beberapa kendaraan berkapasitas sama untuk mengunjungi beberapa pelanggan dengan batas waktu tertentu. Sebagian besar penelitian VRP sebelumnya hanya meminimalkan jarak total sebagai objektif tunggal, tanpa mempertimbangkan keseimbangan jarak antar rute yang dihasilkan. Untuk ini diperlukan solusi terhadap permasalahan VRP yang mempertimbangkan faktor keseimbangan jarak antar rute selain batasan yang hanya melibatkan faktor minimalisasi total jarak rute. Dalam penelitian ini dikembangkan algoritma hiperheuristik untuk menyelesaikan permasalahan VRP dengan objektif jamak, yaitu algoritma yang mengombinasikan objektif untuk meminimalkan total jarak rute dan objektif untuk menyeimbangkan jarak antar rute yang dihasilkan. Parameter keseimbangan antar jarak antar rute diukur menggunakan formulasi simpangan baku terhadap masing-masing rute yang dihasilkan. Metode pareto sorting digunakan untuk menghasilkan solusi yang efektif berdasarkan nilai kedua fungsi objektif, indikator jumlah solusi, serta nilai coverage dan nilai hypervolume dari solusi. Algoritma hiperheuristik yang telah berhasil dikembangkan dalam penelitian ini diimplementasikan dengan menggunakan kerangka kerja HyFlex dan bahasa pemrograman Java. Uji coba hasil implementasi dilakukan menggunakan dua set data dengan kompleksitas yang berbeda, yaitu set data Solomon dan set data Gehring dan Homberger. Metode pemilihan low-level heuristic berbasis algoritma hill climbing hyperheuristic dipilih karena memberikan solusi yang lebih baik dibandingkan dengan algoritma great deluge hyperheuristic. Hasil uji coba perbandingan antara solusi VRP dengan objektif jamak dan solusi VRP dengan objektif tunggal menunjukkan bahwa rerata simpangan baku jarak antar rute untuk VRP dengan objektif jamak (sebesar 678) cukup jauh lebih rendah dibandingkan rerata simpangan baku antar rute VRP dengan objektif tunggal (sebesar 1.053), walaupun rerata total jarak minimum yang dihasilkan oleh VRP dengan objektif jamak (sebesar 99.590) relatif lebih besar dibandingkan dengan yang dihasilkan oleh VRP dengan objektif tunggal (sebesar 94.650). Hal ini menunjukkan bahwa tambahan fungsi objektif untuk menyeimbangkan jarak antar rute kendaraan dari solusi VRP yang dihasilkan sesuai dengan tujuan penelitian. ========================================================================================================================Vehicle Routing Problem (VRP) is one of the combinatoric problems hard to solve. VRP aims to generate a set of the shortest routes of vehicles with similar capacity to visit customers with certain time limit. Most previous VRP studies only minimized total distance as a single objective, regardless of the balance of route distances. Therefore, it required a solution to the VRP that considered the balance factor of distance between routes other than minimizing the total distance of the route. In this study, hyper-heuristic algorithm was developed to solve VRP with multi-objective, an algorithm that combines objective function to minimize the total distance of the routes and objective function to balance of obtained route distances. The balance of route distances parameter was measured by standard deviation formulation of route distances. Pareto sorting method was used to generate effective solutions based on the value of the two objective functions, the number of solutions indicators, the coverage value and hypervolume value of the solutions. The developed hyper-heuristic algorithm was implemented using HyFlex framework and Java programming. The experiments of implemented algorithm utilized two datasets with different complexity, Solomon dataset and Gehring and Homberger dataset. The low-level heuristic selection method based on the hill-climbing hyper-heuristic algorithm was chosen because it provided better solutions than the hyper-heuristic of great deluge algorithm. The comparison of multi-objective VRP solutions and single objective VRP solutions indicated that the average of standard deviation between routes of VRP with multi-objective (678) is considerably lower than the average of standard deviation between routes of VRP with single objective (1,053 ), even though the average of minimum total distance obtained by VRP with multi-objective (99,590) was relatively higher than the average of minimum total distance obtained by VRP with single objective (94,650). It showed that additional objective function for balancing vehicle route distances from obtained VRP solution corresponded to the research objectives

    Rede de retalho num contexto de mudança de paradigma : caso da Galp Energia

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    Mestrado em Métodos Quantitativos para a Decisão Económica e EmpresarialNas empresas, a logística incorpora as tarefas de planeamento e gestão de recursos, revelando-se uma das principais áreas responsável por manter as empresas competitivas. Uma das suas funções, designada por distribuição, tem como objetivo disponibilizar os produtos, no lugar certo, no momento certo e na quantidade certa, sendo necessário otimizar procedimentos para que as operações sejam rentáveis e lucrativas. Neste sentido, surge este relatório, que pretende analisar como é que a atividade de distribuição na empresa Galp Energia pode beneficiar com uma mudança de paradigma. A última alteração do regulamento que fixa os pesos e as dimensões máximos autorizados para os veículos em circulação, possibilita uma renovação na capacidade dos veículos utilizados pela empresa na distribuição dos seus produtos. Assim, a Galp Energia, que se define como uma empresa inovadora e bastante competitiva no mercado da distribuição de produtos petrolíferos, sugere um trabalho académico que viabiliza uma análise do impacto da nova capacidade permitida na sua frota. Como os vários produtos comercializados são distribuídos por diferentes tipos de veículos, a empresa destaca os mais predominantes, isto é, os gasóleos e as gasolinas, designados por combustíveis brancos.In companies, logistics takes on the tasks of planning and resource management, proving to be one of the main areas responsible for keeping companies competitive. One of its roles, called distribution, aims to make the right amount of products available at the right place at the right time, demanding for the optimization of procedures to make operations profitable and lucrative. This leads to this report, with the main purpose of analyzing how the distribution activity at Galp Energia can benefit from a paradigm shifting. The latest amendment to the regulation setting the maximum authorized weights and dimensions for vehicles in circulation, enabled the renewal of the capacity of the vehicles used by the company to distribute its products. Thus, Galp Energia, which defines itself as an innovative and very competitive company in the petroleum products distribution market, suggested an academic work to analyze the impact of the new capacity allowed for its fleet. As the various products sold are distributed by different types of vehicles, the company highlights the most predominant ones, namely diesels and petrols, called white fuels.info:eu-repo/semantics/publishedVersio

    Evolutionary Computation 2020

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    Intelligent optimization is based on the mechanism of computational intelligence to refine a suitable feature model, design an effective optimization algorithm, and then to obtain an optimal or satisfactory solution to a complex problem. Intelligent algorithms are key tools to ensure global optimization quality, fast optimization efficiency and robust optimization performance. Intelligent optimization algorithms have been studied by many researchers, leading to improvements in the performance of algorithms such as the evolutionary algorithm, whale optimization algorithm, differential evolution algorithm, and particle swarm optimization. Studies in this arena have also resulted in breakthroughs in solving complex problems including the green shop scheduling problem, the severe nonlinear problem in one-dimensional geodesic electromagnetic inversion, error and bug finding problem in software, the 0-1 backpack problem, traveler problem, and logistics distribution center siting problem. The editors are confident that this book can open a new avenue for further improvement and discoveries in the area of intelligent algorithms. The book is a valuable resource for researchers interested in understanding the principles and design of intelligent algorithms

    Métodos heurísticos para un problema multicriterio de distribución de ayuda humanitaria

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    Large scale disasters, such as the one caused by the Typhoon Haiyan, which devastated portions of the Philippines in 2013, or the catastrophic 2010 Haiti earthquake, which caused major damage in Port-au-Prince and other settlements in the region, have massive and lasting effects on populations. Nowadays, disasters can be considered as a consequence of inappropriately managed risk. These risks are the product of hazards and vulnerability, which refers to the extent to which a community can be affected by the impact of a hazard. In this way, developing countries, due to their greater vulnerability, suffer the highest costs when a disaster occurs. Disaster relief is a challenge for politics, economies, and societies worldwide. Humanitarian organizations face multiple decision problems when responding to disasters. In particular, once a disaster strikes, the distribution of humanitarian aid to the population affected is one of the most fundamental operations in what is called humanitarian logistics. This term is defined as the process of planning, implementing and controlling the effcient, cost-effective ow and storage of goods and materials as well as related information, from the point of origin to the point of consumption, for the purpose of meeting the end bene- ciaries' requirements and alleviate the suffering of vulnerable people, [the Humanitarian Logistics Conference, 2004 (Fritz Institute)]. During the last decade there has been an increasing interest in the OR/MS community in studying this topic, pointing out the similarities and differences between humanitarian and business logistics, and developing models suited to handle the special characteristics of these problems. Several authors have pointed out that traditional logistic objectives, such as minimizing operation cost, are not the most relevant goals in humanitarian operations. Other factors, such as the time of operation, or the design of safe and equitable distribution plans, come to the front, and new models and algorithms are needed to cope with these special features. Up to six attributes related to the distribution plan are considered in our multi-criteria approach. Even though there are usually simple ways to measure the cost of an operation, the evaluation of some other attributes such as security or equity is not easy. As a result, several attribute measures are proposed and developed, focusing on different aspects of the solutions. Furthermore, when metaheuristic solution methods are used, considering non linear objective functions does not increase the complexity of the algorithms significantly, and thus more accurate measures can be utilized..
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