Clustering search

This paper presents the Clustering Search (CS) as a new hybrid metaheuristic, which works in conjunction with other metaheuristics, managing the implementation of local search algorithms for optimization problems. Usually the local search is costly and should be used only in promising regions of the search space. The CS assists in the discovery of these regions by dividing the search space into clusters. The CS and its applications are reviewed and a case study for a problem of capacitated clustering is presented.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Universidade Federal do MaranhãoUniversidade Federal de São Paulo (UNIFESP)Instituto Nacional de Pesquisas EspaciaisUNIFESPSciEL

Decentralized Cooperative Metaheuristic for the Dynamic Berth Allocation Problem

The increasing demand of maritime transport and the great competition among port terminals force their managers to reduce costs by exploiting its resources accurately. In this environment, the Berth Allocation Problem, which aims to allocate and schedule incoming vessels along the quay, plays a relevant role in improving the overall terminal productivity. In order to address this problem, we propose Decentralized Cooperative Metaheuristic (DCM), which is a population-based approach that exploits the concepts of communication and grouping. In DCM, the individuals are organized into groups, where each individual shares information with its group partners. This grouping strategy allows to diversify as well as intensify the search in some regions by means of information shared among the individuals of each group. Moreover, the constrained relation for sharing information among individuals through the proposed grouping strategy allows to reduce computational resources in comparison to the `all to all' communication strategy. The computational experiments for this problem reveal that DCM reports high-quality solutions and identifies promising regions within the search space in short computational times

A modified sailfish optimizer to solve dynamic berth allocation problem in conventional container terminal

During the past two decades, there has been an increase on maritime freight traffic particularly in container flow. Thus, the Berth Allocation Problem (BAP) can be considered among the primary optimization problems encountered in port terminals. In this paper, we address the Dynamic Berth Allocation Problem (DBAP) in a conventional layout terminal which differs from the popular discrete layout terminal in that each berth can serve multiple vessels simultaneously if their total length is equal or less than the berth length. Then, a Modified Sailfish Optimizer (MSFO) meta-heuristic based on hunting sailfish behavior is developed as an alternative for solving this problem. Finally, computational experiments and comparisons are presented to show the efficiency of our method against other methods presented in the literature in one hand. We also discuss the productivity of a container terminal based on different scenarios which can happen

Modelo Matemático para o Planejamento de Atracação de Navios Liners com Possibilidade de Cancelamento de Escala.

Os portos brasileiros movimentam mais de 90% das cargas internacionais do país, com destaque para a movimentação de contêineres que vem crescendo ano a ano no Brasil e já representam 10,4% de toda a carga movimentada. Os navios de contêineres são usualmente contratados pela categoria de serviço liners. Os navios liners possuem uma escala fixa de atendimento, previamente divulgada, e caso o navio não seja atracado no porto dentro do intervalo acordado de tempo entre sua chegada até sua atracação, denominado janela de atracação, ocorre uma situação chamada cancelamento de escala e o navio simplesmente não atraca no porto e segue viagem para não comprometer todas as escalas nos outros portos. Portanto, no contexto analisado, é importante disponibilizar aos portos uma ferramenta que minimize o cancelamento de escala, pois tal cancelamento impactará em perdas de receita e contratos para o porto. Para o planejamento da atracação de navios no porto, a literatura cientifica sugere o Problema de Alocação de Berço (PAB). Esta dissertação tem por objetivo propor um modelo matemático baseado no Problema de Roteamento de Veículos (PRV) com Prêmio, Janela de Tempo e Múltiplos Depósitos aplicado ao planejamento da atracação em portos de navios liners com possibilidade de cancelamento de escala visando maximizar a receita obtida pelo atendimento aos navios e também reduzir o tempo de espera para o navio atracar. Instâncias de teste foram desenvolvidas tendo como base as características operacionais do Terminal de Vila Velha (TVV) e o modelo foi executado no CPLEX 12.6. Os resultados mostraram a eficiência do modelo proposto para planejamento da atracação em portos onde pode haver o cancelamento de escala, reduzindo o número de navios não atendidos e maximizando a receita do porto

Minimizing the Total Service Time of Discrete Dynamic Berth Allocation Problem by an Iterated Greedy Heuristic

Berth allocation is the forefront operation performed when ships arrive at a port and is a critical task in container port optimization. Minimizing the time ships spend at berths constitutes an important objective of berth allocation problems. This study focuses on the discrete dynamic berth allocation problem (discrete DBAP), which aims to minimize total service time, and proposes an iterated greedy (IG) algorithm to solve it. The proposed IG algorithm is tested on three benchmark problem sets. Experimental results show that the proposed IG algorithm can obtain optimal solutions for all test instances of the first and second problem sets and outperforms the best-known solutions for 35 out of 90 test instances of the third problem set

Models and Solutions Algorithms for Improving Operations in Marine Transportation

International seaborne trade rose significantly during the past decades. This created the need to improve efficiency of liner shipping services and marine container terminal operations to meet the growing demand. The objective of this dissertation is to develop simulation and mathematical models that may enhance operations of liner shipping services and marine container terminals, taking into account the main goals of liner shipping companies (e.g., reduce fuel consumption and vessel emissions, ensure on-time arrival to each port of call, provide vessel scheduling strategies that capture sailing time variability, consider variable port handling times, increase profit, etc.) and terminal operators (e.g., decrease turnaround time of vessels, improve terminal productivity without significant capital investments, reduce possible vessel delays and associated penalties, ensure fast recovery in case of natural and man-made disasters, make the terminal competitive, maximize revenues, etc.). This dissertation proposes and models two alternatives for improving operations of marine container terminals: 1) a floaterm concept and 2) a new contractual agreement between terminal operators. The main difference between floaterm and conventional marine container terminals is that in the former case some of import and/or transshipment containers are handled by off-shore quay cranes and placed on container barges, which are further towed by push boats to assigned feeder vessels or floating yard. According to the new collaborative agreement, a dedicated marine container terminal operator can divert some of its vessels for the service at a multi-user terminal during specific time windows. Another part of dissertation focuses on enhancing operations of liner shipping services by introducing the following: 1) a new collaborative agreement between a liner shipping company and terminal operators and 2) a new framework for modeling uncertainty in liner shipping. A new collaborative mechanism assumes that each terminal operator is able to offer a set of handling rates to a liner shipping company, which may result in a substantial total route service cost reduction. The suggested framework for modeling uncertainty is expected to assist liner shipping companies in designing robust vessel schedules

Um algoritmo de busca híbrido para o problema de roteamento de embarcações de suprimento periódico

High quality maritime petroleum transportation is critical to ensure timely flow of goods, reducing the total logistics cost and guaranteeing an efficient process. In this thesis, we focus on the transportation of deck cargo to offshore units as observed in the operations of our industrial partner in Rio de Janeiro, Brazil. The main objective of this research is to define the maritime routes to solve a periodic supply vessels routing problem, taking into account the port departure and opening hours at the offshore facilities. We describe the solution procedures currently used by the company, and we formally formulate the problem mathematically. Given that the sizes of the instances are too large to be solved exactly, we propose different methods to achieve better solutions with a reduced computational time. The first method, composed of three phases, uses a clustering heuristic combined with an exact method in order to perform the routing and ends with a resenquencing according to the operating hours, port departures and time between services constraits. The second method uses the adaptive large neighborhood search (ALNS) heuristic in an attempt to reduce the number of operations performed by the previous heuristic and the computational time. Finally, a hybrid method is proposed based on the ALNS heuristic and innovates with the concepts of the clustering search algorithm that proposes a detection of promising regions of the search space. The computational results indicate that the hybrid heuristic brings benefits to the ALNS by finding better solutions in less time and still reduces the coefficient of variation within a sample of solutions in different executions.O transporte marítimo de petróleo de alta qualidade é fundamental para assegurar um fluxo de mercadorias dentro do prazo previsto, reduzindo o custo total da logística e garantindo operações eficientes. Nesta tese, o focus está no transporte de carga de convés para unidades marítimas como observado nas operações do parceiro industrial no Rio de Janeiro, Brasil. O principal objetivo desta pesquisa é definir as rotas marítimas para resolver um problema de roteamento de embarcações de suprimento periódico, levando em consideração a programação do porto e o horário de abertura em algumas instalações. Os procedimentos atualmente utilizados pela empresa são descritos, e o problema é matematicamente formulado. Dado que o tamanho das instâncias é muito grande para serem resolvidos exatamente, propõem-se diferentes métodos visando alcançar melhores soluções com um baixo tempo computacional. O primeiro método, composto por três fases, usa uma heurística de agrupamento de unidades marítimas combinada a um método exato a fim de realizar o roteamento das mesmas e finaliza com o sequenciamento das rotas de acordo com as restrições de horários de funcionamento, partidas do porto e tempo entre atendimentos. O segundo método utiliza a heurística adaptive large neighborhood search (ALNS) na tentativa de reduzir a quantidade de operações realizadas pela heurística anterior e o tempo computacional. Por fim, propõe-se um método híbrido baseando-se na heurística ALNS e inovando com conceitos do algoritmo clustering search que propõe uma detecção de regiões promissoras do espaço de busca. Os resultados computacionais indicam que a heurística híbrida traz benefícios ao ALNS ao encontrar melhores soluções em menos tempo e ainda reduz o coeficiente de variação dentro de uma amostra de soluções em diferentes execuções

Kerjasama Pemanfaatan Prasarana dan Sarana Terminal Dalam Upaya Mengurangi Waktu Pelayanan Kapal Di Terminal Peti Kemas

Berth allocation problem merupakan permasalahan yang kompleks karena adanya faktor ketidakpastian (uncertainty) yang menyebabkan kedatangan kapal di pelabuhan sulit untuk diprediksi dan seringkali terlambat dari jadwal yang telah ditentukan. Keterlambatan kedatangan kapal mengakibatkan sumber daya yang sudah dipersiapkan menjadi menganggur. Operator terminal harus menyusun jadwal ulang untuk mengalokasikan kapal yang mengalami keterlambatan. Apabila sumber daya tidak tersedia maka kapal harus menunggu (antri) sampai dermaga tersedia. Berth allocation tidak semata-mata hanya mengalokasikan kapal ke dermaga, tetapi juga mengalokasikan sumber daya lainnya seperti crane, yard, RTG, dan alat transportasi. Untuk pelabuhan yang memiliki lebih dari satu terminal yang dioperasikan oleh operator berbeda dimana setiap terminal menerapkan sistem windows slot, setiap terminal memiliki potensi pada saat yang sama di satu terminal terjadi kekurangan (shortage) dan terminal lain terjadi kelebihan (surplus) sumber daya. Oleh karena itu dibutuhkan strategi untuk menghadapi kondisi tersebut. Salah satu strategi yang diusulkan adalah dengan melakukan kerja sama atau kolaborasi. Pada kondisi eksisting shipping lines yang memiliki windows slot di satu terminal hanya bisa berthing dan bongkar muat menggunakan sumber daya yang dimiliki terminal tersebut. Apabila seluruh dermaga dan sumber daya di terminal tersebut sedang digunakan, maka kapal yang datang harus menunggu dan antri sampai dermaga tersedia, meskipun di terminal lain terdapat dermaga yang tidak digunakan, demikian juga sebaliknya. Strategi kolaborasi memungkinkan setiap kapal bisa berthing di setiap terminal meskipun kapal tersebut memiliki windows di terminal yang berbeda. Dalam penelitian ini dikembangkan model simultaneous berth allocation problem dengan strategi kolaborasi. Karena sistem yang dimodelkan relatif kompleks dan mengandung unsur ketidakpastian maka dalam studi ini digunakan permodelan discrete event simulation. Beberapa skenario diusulkan dan dipilih skenario terbaik yang terbaik. Skenario ditentukan berdasarkan kombinasi empat faktor, yaitu service order, berth-yard, crane dan strategy, dimana setiap faktor memiliki 2 level. Dengan menggunakan konsep full factorial design (2k factorial design) dihasilkan sebanyak 16 skenario. Skenario pertama merupakan kondisi eksisting yang dijadikan sebagai baseline untuk menentukan skenario terbaik yang ditentukan berdasarkan dua respon, yaitu waktu (waiting time, handling time, turnaround time) dan jumlah kapal yang menunggu. Berdasarkan hasil simulasi diperoleh skenario terbaik dengan kombinasi service order secara menggunakan sistem prioritas, berth-yard secara independent, alokasi crane secara fixed, dan strategi yang digunakan adalah kolaborasi. Hasil simulasi menunjukkan bahwa kolaborasi dapat menciptakan keseimbangan operasi di terminal dengan load tinggi dan terminal dengan load rendah. Waiting time dan turnaround time di terminal dengan load tinggi menjadi lebih pendek, sedangkan di terminal dengan load rendah menjadi lebih panjang. Strategi kolaborasi dapat mengurangi jumlah kapal menunggu hingga 43.82 % per tahun, menurunkan waiting time sebesar 46.82%, dan menurunkan turnaround time sebesar 10.60% per kapal per kedatangan. Kolaborasi menimbulkan terjadinya shifting kapal dan container dari terminal load tinggi ke terminal load rendah. Pergeseran kapal dan container menyebabkan terjadinya perubahan performa finansial bagi kedua terminal. Untuk menghindarkan terjadinya kerugian bagi salah satu pihak, maka dibuat skema profit sharing atau profit redistribution. ================================================================================================================== Berth allocation problem is a complex problem because of the uncertainty factor that causes the arrival of the ship in the port is difficult to predict and often the arrival of the ship is late from the schedule.The ship's delays result in the resources already allocated for the vessel cannot be utilized. If the ship comes out of schedule, the terminal operator should re-schedule the ship, so the ship must wait until the berth is available. Berth allocation does not solely allocate ships to berth, but also allocates other resources such as cranes, yards, RTG and transportation. For ports that have more than one terminal operated by different operators and each terminal implements a windows system, each terminal has the potential at the same time in one terminal to have a shortage of resources and another terminal overload (surplus). Strategy is needed to deal with the condition. One of the proposed strategies is to collaborate between terminals. In the existing condition of shipping lines that have windows in one terminal can only berthing, loading and unloading using resources in the terminal. If all the resources at the terminal are in use, the arriving vessel will have to wait and queue until the berth is available, even in other terminals there are unused docks, and vice versa. The collaboration strategy allows each ship to berthing in every terminal even though it has windows in different terminals. The allocation of berth, crane and yard is an interrelated process so that the allocation cannot be done partially or gradually (multiphase). Partial and multiphase solutions are generally accomplished by completing the berth allocation in the first phase, and continued with the crane or yard allocation in the next phase. Multiphase solutions have drawbacks because they do not always result in optimal completion. The allocation of berth, crane and yard is an interrelated process so that the allocation cannot be done partially or gradually (multiphase). Partial and multiphase solutions are generally accomplished by completing the berth allocation in the first phase, and continued with the crane or yard allocation in the next phase. Multiphase solutions have drawbacks because they do not always result in optimal completion. The optimal crane allocation in the second phase can change the optimal berth allocation in the first phase. This research develops simultaneous berth allocation problem model with collaboration strategy. Because the modeled system is relatively complex and contains uncertainty factor, this study uses discrete event simulation model. In this simulation, 16 scenarios were obtained using the full factorial design concept (2k factorial design) from a combination of four factors: service order, berth-yard, crane and strategy, each factor has two levels. The first scenario is an existing condition that is used as a baseline to determine the best scenario. The best scenario is determined based on two responses, namely time (waiting time, handling time, turnaround time) and the number of ships waiting. Simulation results show that collaboration can create a balance of operations in terminals with high load and terminals with low load. Waiting time and turnaround time in terminals with high load becomes shorter, while in terminals with low load becomes longer. The collaboration strategy can reduce the number of ships waiting up to 43.82% per year, while the waiting time is reduced by 46.82%. Turnaround time decreased by 10.60% per ship per arrival. Collaboration creates unavoidable consequences of shifting ships and containers from high load terminals to low load terminals. Shifting vessels and containers leads to changes in financial performance for both terminals. In this research also created profit sharing scheme or profit redistribution to avoid losses for either party

Multi-Objective and Multi-Attribute Optimisation for Sustainable Development Decision Aiding

Optimization is considered as a decision-making process for getting the most out of available resources for the best attainable results. Many real-world problems are multi-objective or multi-attribute problems that naturally involve several competing objectives that need to be optimized simultaneously, while respecting some constraints or involving selection among feasible discrete alternatives. In this Reprint of the Special Issue, 19 research papers co-authored by 88 researchers from 14 different countries explore aspects of multi-objective or multi-attribute modeling and optimization in crisp or uncertain environments by suggesting multiple-attribute decision-making (MADM) and multi-objective decision-making (MODM) approaches. The papers elaborate upon the approaches of state-of-the-art case studies in selected areas of applications related to sustainable development decision aiding in engineering and management, including construction, transportation, infrastructure development, production, and organization management