A binary particle swarm optimization algorithm for ship routing and scheduling of liquefied natural gas transportation

With the increasing global demands for energy, fuel supply management is a challenging task of today’s industries in order to decrease the cost of energy and diminish its adverse environmental impacts. To have a more environmentally friendly fuel supply network, Liquefied Natural Gas (LNG) is suggested as one of the best choices for manufacturers. As the consumption rate of LNG is increasing dramatically in the world, many companies try to carry this product all around the world by themselves or outsource it to third-party companies. However, the challenge is that the transportation of LNG requires specific vessels and there are many clauses in related LNG transportation contracts which may reduce the revenue of these companies, it seems essential to find the best option for them. The aim of this paper is to propose a meta-heuristic Binary Particle Swarm Optimization (BPSO) algorithm to come with an optimized solution for ship routing and scheduling of LNG transportation. The application demonstrates what sellers need to do to reduce their costs and increase their profits by considering or removing some obligations

An operational model for liquefied natural gas spot and arbitrage sales

As more buyers become interested in the spot purchase of liquefied natural gas (LNG), the share of spot trade in LNG business increases. This means that the cash flowing into the upstream of LNG projects is a combination of that generated by deliveries to long-term contract (LTC) customers and uncommitted product and arbitrage spot sales. LTC cash flows are more predictable while uncommitted product and arbitrage cash flows, affected by the dynamics of supply and demand, are more volatile and therefore less predictable. In this research, we formulate an inventory routing problem (IRP) which maximizes the profit of an LNG producer with respect to uncommitted product and arbitrage spot sales, and also LTC deliveries at an operational level. Using the model, the importance of arbitrage, interest rates and compounding frequency in profit maximization, and also the significance of interest rates and fluctuation in spot prices in decision-making for spot sales of uncommitted product are studied. It is proven that writing traditional LTCs with relaxed destination clauses which assist in arbitrage is beneficial to the LNG producer. However, in contrast to what was predicted neither the interest rate nor the compounding frequency has any importance in profit maximization when no change of selling strategy is observed. Apart from these, it is shown that there is a trade-off between the expectation of higher spot prices and the inventory and shipping costs in decision-making for spot sales of uncommitted product in the LNG industry. Finally, it is observed that the interest rate can affect the set of decisions on spot sales of uncommitted product, although the importance of such changes in profit remains to be further explored

Modelos de otimização para a distribuição de combustíveis em curta distância marítima

Doutoramento em Matemática e AplicaçõesO transporte marítimo e o principal meio de transporte de mercadorias em todo o mundo. Combustíveis e produtos petrolíferos representam grande parte das mercadorias transportadas por via marítima. Sendo Cabo Verde um arquipelago o transporte por mar desempenha um papel de grande relevância na economia do país. Consideramos o problema da distribuicao de combustíveis em Cabo Verde, onde uma companhia e responsavel por coordenar a distribuicao de produtos petrolíferos com a gestão dos respetivos níveis armazenados em cada porto, de modo a satisfazer a procura dos varios produtos. O objetivo consiste em determinar políticas de distribuicão de combustíveis que minimizam o custo total de distribuiçao (transporte e operacões) enquanto os n íveis de armazenamento sao mantidos nos n íveis desejados. Por conveniencia, de acordo com o planeamento temporal, o prob¬lema e divido em dois sub-problemas interligados. Um de curto prazo e outro de medio prazo. Para o problema de curto prazo sao discutidos modelos matemáticos de programacao inteira mista, que consideram simultaneamente uma medicao temporal cont ínua e uma discreta de modo a modelar multiplas janelas temporais e taxas de consumo que variam diariamente. Os modelos sao fortalecidos com a inclusão de desigualdades validas. O problema e então resolvido usando um "software" comercial. Para o problema de medio prazo sao inicialmente discutidos e comparados varios modelos de programacao inteira mista para um horizonte temporal curto assumindo agora uma taxa de consumo constante, e sao introduzidas novas desigualdades validas. Com base no modelo escolhido sao compara¬das estrategias heurísticas que combinam três heur ísticas bem conhecidas: "Rolling Horizon", "Feasibility Pump" e "Local Branching", de modo a gerar boas soluçoes admissíveis para planeamentos com horizontes temporais de varios meses. Finalmente, de modo a lidar com situaçoes imprevistas, mas impor¬tantes no transporte marítimo, como as mas condicões meteorológicas e congestionamento dos portos, apresentamos um modelo estocastico para um problema de curto prazo, onde os tempos de viagens e os tempos de espera nos portos sao aleatórios. O problema e formulado como um modelo em duas etapas, onde na primeira etapa sao tomadas as decisões relativas as rotas do navio e quantidades a carregar e descarregar e na segunda etapa (designada por sub-problema) sao consideradas as decisoes (com recurso) relativas ao escalonamento das operacões. O problema e resolvido por um metodo de decomposto que usa um algoritmo eficiente para separar as desigualdades violadas no sub-problema.Maritime transportation is a major mode of transportation of goods worldwide. Most of cargo of the maritime transport accounted for liquid cargo oil and petroleum products. As Cape Verde is an archipelago, maritime transportation is of great importance for the local economic activity. We consider a fuel oil distribution problem where an oil company is responsible for the coordination of the distribution of oil products with the inventory management of those products at ports in order to satisfy the demands for the several oil products. The objective is to determine distribution policies that minimize the routing and operating costs, while inventory levels are maintained within given limits. For convenience, the planning problem is divided into two related subproblems accordingly to the length of the planning horizon: A short- term and medium-term planning. For the short-term planning problem we discuss mathematical mixed integer programming models that combine continuous and discrete time measures in order to handle with multiple time windows and a daily varying consumption rate of the various oil products. These models are strengthened with valid inequalities. Then the problem is solved using a commercial software. For the second subproblem several mixed integer formulations are discussed and compared for a short time horizon, and assuming constant consumption rates and new valid inequalities are introduced. Then, based on the chosen model, we compare several heuristic strategies that combine the well-known Rolling Horizon, Feasibility Pump and Local Branching heuristics, in or¬der to derive good feasible solutions for planning horizons of several months. Finally, as weather conditions and ports congestion are very impor¬tant in maritime transportation, we present a stochastic model for a short sea shipping problem, where traveling and waiting time are random. The problem is formulated as a two stage recourse problem, where in the first stage the routing and the load/unload quantities are defined, and in the second stage (subproblem) the scheduling of operations is determined. The problem is solved by a decomposition method that uses an efficient separation algorithm to include inequalities from the subproblem

Combining Strategic and Operational Decision Making in Liquefied Natural Gas (LNG) Logistics

Recent increase in energy prices, concern regarding CO2 emissions, exploration of new energy sources, and some conventional methods of Liquefied Natural Gas transportation have a significant impact on LNG trade to make it more competitive in the energy market. This results in a lot of investment for LNG value chain. For profitable operations such LNG logistics, it is necessary to find the optimal design in terms of the supply chain associated with it. Of special interests are finding an optimal schedule for LNG delivery by ships from production terminal to regas terminals and satisfying inventory and port constraints by minimizing total cost and selecting an optimal combination of contracts and suppliers. This can be possible by modelling a combination of the inventory routing problem (LNG-IRP) and the model to minimize procurement cost by selection of LNG contracts that varies in price formulation, duration, quality etc. These various cost factors in the objective makes the combined model more challenging. To find the lowest cost solution for the model, optimization-based approaches can be very useful. Therefore, in this paper, we address these circumstances by proposing a mixed-integer linear programming model that helps the buyers select the best combination of suppliers and contract, and based on selecting amount of contract, buyer’s demand (inventory capacity) in each regas terminal is satisfied by minimizing stock out, unmet demand, and losts production.M.S., Supply Chain Management and Logistics -- Drexel University, 201

Discrete time and continuous time formulations for a short sea inventory routing problem

We consider a fuel oil distribution problem where an oil company is responsible for the routing and scheduling of ships between ports such that the demand for various fuel oil products is satisfied during the planning horizon. The production/consumption rates are given and assumed to be constant. We provide two alternative mixed integer formulations: a discrete time model adapted from the case where the production/consumption rates are varying and a classical continuous time formulation. We discuss different extended formulations and valid inequalities that allow us to reduce the linear gap of the two initial formulations. A computational study comparing the various models accordingly to their size, linear gap and running time, was conducted based on real small-size instances, using a commercial software

Long‐term effects of short planning horizons for inventory routing problems

This paper presents a detailed study concerning the importance of the planning horizon when solving inventory routing problems (IRPs). We evaluate the quality of decisions obtained by solving a finite-horizon IRP. We also discuss the relevance of explicitly considering profit maximization models rather than the traditional cost minimization variant. As a means to this end, we describe four classes of the IRP corresponding to different types of markets. Two of them lead to nonlinear models, which are linearized. Furthermore, we provide a deterministic simulator to evaluate the long-term effects arising from using planning horizons of varying lengths when solving the IRP. A computational study is performed on cases generated from benchmark data instances. The results confirm that the long-term performance of the IRP decisions is, in part, contingent on the length of the selected planning horizon. They also show that considering profit maximization instead of cost minimization leads to different decisions, generating considerably more revenue and profits, albeit not nearly as much as suggested by individual solutions to static IRPs with short planning horizons. Keywords: profit maximization, path flow, linearization, end effect, simulationpublishedVersio

Techno‑economic analysis of natural gas distribution using a small‑scale liquefied natural gas carrier

The design of the gas distribution for small-demand power plants located on remote islands is logistically challenging. The use of small-scale liquefied natural gas (LNG) vessels can be an option for these logistic problems. This paper aims to conduct a techno-economic analysis of using small-scale LNG vessels for gas distribution to the power plants that are spread across different islands. Route optimisation has been conducted using the capacitated vehicle routing problem method. The ship’s principal dimensions were determined using the aspect ratio from a linear regression of existing small-scale LNG vessels. As a case study, the gas demands for a gas power plant in eastern Indonesia were analysed into four distribution clusters. The results of the techno-economic analysis showed that the four distribution clusters have different characteristics regarding the LNG requirements, location characteristics and ship specifications. The capacity of small-scale LNG vessels feasible in terms of technical aspects varies from 2500, 5000, to > 10,000 m3 with variations in the ship speed depending on the location of the power plants. The amount of cargo requested and the shipping distance was affected to the cost of LNG transportation. The economic assessment proposes that the feasible investment by considering small-scale LNG cargo distribution, from the case study shows that with a ship capacity of 5000 m3 feasible margin rate is ≥ 3 USD/metric million British thermal units with an internal rate of return of 10% and estimated payback period is less than 15 years

A concise guide to existing and emerging vehicle routing problem variants

Vehicle routing problems have been the focus of extensive research over the past sixty years, driven by their economic importance and their theoretical interest. The diversity of applications has motivated the study of a myriad of problem variants with different attributes. In this article, we provide a concise overview of existing and emerging problem variants. Models are typically refined along three lines: considering more relevant objectives and performance metrics, integrating vehicle routing evaluations with other tactical decisions, and capturing fine-grained yet essential aspects of modern supply chains. We organize the main problem attributes within this structured framework. We discuss recent research directions and pinpoint current shortcomings, recent successes, and emerging challenges