Routing of Supply Vessels to with Deliveries and Pickups of Multiple Commodities

AbstractThis paper considers a single vehicle routing problem with pickups and deliveries of multiple commodities where each customer requires both pickup and delivery of several types of goods from a single depot. This problem arises in offshore upstream logistics and is relevant for the oil and gas companies operating offshore. Offshore installations need to be supplied with several types of goods from an onshore base, and also some cargo need to be transported from the installations back to the base. Supply operations from and to the base are performed by supply vessels, which have separate compartments for different types of cargo. In this paper we present a mathematical formulation for the problem and describe a metaheuristic algorithm yielding non- Hamiltonian routes where customers may be visited once or twice. Computational tests show that the algorithm outperforms CPLEX optimization solver in speed on instances of medium size and generates high quality solutions for large-size instances compared to the Unified Tabu Search algorithm

Periodic supply vessel planning under demand and weather uncertainty

We solve a periodic supply vessel planning problem under demand and weather uncertainty, arising in offshore of oil and gas production. Our study is motivated by the case of the Norwegian energy operator Equinor which supplied us with data. The aim is to determine an optimal fleet composition and a least-cost vessel schedule under uncertain demand at the installations and uncertain weather conditions. We present a methodology incorporating a metaheuristic within a discrete-event simulation model which, applied iteratively for the increasing values of reliability level parameters, yields a vessel schedule of least expected cost

Supply vessel routing and scheduling under uncertain demand

We solve a supply vessel planning problem arising in upstream offshore petroleum logistics. A fleet of supply vessels delivers all the necessary equipment and materials to a set of offshore installations from an onshore supply base, according to a delivery schedule or sailing plan. Supply vessels, being the major cost contributor, are chartered on a long-term basis. The planning of supply vessels implies resolving the trade-off between the cost of the delivery schedule and the reliability of deliveries on the scheduled voyages, i.e. the service level. The execution of a sailing plan is affected by stochastic demands at the installations since a high demand fluctuation quite often leads to insufficient vessel capacity to perform a voyage according to the sailing plan. In addition, the average demand level at the installations may change over time, while the number of vessels in the sailing plan remains the same. Maintaining a reliable flow of supplies under stochastic demand therefore leads to additional costs and reduced service level. We present a novel methodology for reliable supply vessel planning and scheduling, enabling planners to construct delivery schedules having a low expected total cost. The methodology involves the construction of delivery schedules with different reliability levels using an adaptive large neighborhood search metaheuristic algorithm combined with a discrete event simulation procedure for the computation of the expected solution cost. Keywords: maritime logistics, supply vessel planning, recourse, reliable vessel schedules, metaheuristic, simulationpublishedVersio

Congestion management in the Nordic power market : nodal pricing versus zonal pricing

In the Nordic day-ahead electricity market zonal pricing or market splitting is used for relieving congestion between a predetermined set of price areas. This congestion management method represents an aggregation of individual connection points into price areas, and flows in the actual electricity network are only partially represented in the market clearing. Because of several strained situations in the power system during 2009 and 2010, changes in the congestion management method are under consideration by the Norwegian regulator NVE. We discuss three different congestion management methods – nodal pricing, and optimal and simplified zonal pricing. Four hourly cases from 2010 are used to illustrate the effects of different congestion management methods on prices, surpluses and network utilization

Periodic supply vessel planning under demand and weather uncertainty

We solve a periodic supply vessel planning problem under demand and weather uncertainty, arising in offshore of oil and gas production. Our study is motivated by the case of the Norwegian energy operator Equinor which supplied us with data. The aim is to determine an optimal fleet composition and a least-cost vessel schedule under uncertain demand at the installations and uncertain weather conditions. We present a methodology incorporating a metaheuristic within a discrete-event simulation model which, applied iteratively for the increasing values of reliability level parameters, yields a vessel schedule of least expected cost

Minimization of passenger takeoff and landing risk in offshore helicopter transportation: models, approaches and analysis

Offshore petroleum industry uses helicopters to transport the employees to and from installations. Takeoff and landing represent a substantial part of the flight risks for passengers. In this paper, we propose and analyze approaches to create a safe flight schedule to perform pickup of employees by several independent flights. Two scenarios are considered. Under the non-split scenario, exactly one visit is allowed to each installation. Under the split scenario, the pickup demand of an installation can be split between several flights. Interesting links between our problem and other problems of combinatorial optimization, e.g., parallel machine scheduling and bin-packing are established. We provide worst-case analysis of the performance of some of our algorithms and report the results of computational experiments conducted on randomly generated instances based on the real sets of installations in the oil fields on the Norwegian continental shelf. This paper is the first attempt to handle takeoff and landing risk in a flight schedule that consists of several flights and lays ground for the study on more advanced and practically relevant models

An estimation of distribution algorithm for lot-streaming flow shop problems with setup times

Lot-streaming flow shops have important applications in different industries including textile, plastic, chemical, semiconductor and many others. This paper considers an n-job m-machine lot-streaming flow shop scheduling problem with sequence-dependent setup times under both the idling and noidling production cases. The objective is to minimize the maximum completion time or makespan. To solve this important practical problem, a novel estimation of distribution algorithm (EDA) is proposed with a job permutation based representation. In the proposed EDA, an efficient initialization scheme based on the NEH heuristic is presented to construct an initial population with a certain level of quality and diversity. An estimation of a probabilistic model is constructed to direct the algorithm search towards good solutions by taking into account both job permutation and similar blocks of jobs. A simple but effective local search is added to enhance the intensification capability. A diversity controlling mechanism is applied to maintain the diversity of the population. In addition, a speed-up method is presented to reduce the computational effort needed for the local search technique and the NEH-based heuristics. A comparative evaluation is carried out with the best performing algorithms from the literature. The results show that the proposed EDA is very effective in comparison after comprehensive computational and statistical analyses.This research is partially supported by the National Science Foundation of China (60874075, 70871065), and Science Foundation of Shandong Province in China under Grant BS2010DX005, and Postdoctoral Science Foundation of China under Grant 20100480897. Ruben Ruiz is partially funded by the Spanish Ministry of Science and Innovation, under the project "SMPA-Advanced Parallel Multiobjective Sequencing: Practical and Theoretical Advances" with reference DPI2008-03511/DPI and by the IMPIVA-Institute for the Small and Medium Valencian Enterprise, for the project OSC with references IMIDIC/2008/137, IMIDIC/2009/198 and IMIDIC/2010/175.Pan, Q.; Ruiz García, R. (2012). An estimation of distribution algorithm for lot-streaming flow shop problems with setup times. Omega. 40(2):166-180. https://doi.org/10.1016/j.omega.2011.05.002S16618040

Peak price hours in the Nordic power market winter 2009/2010: effects of pricing, demand elasticity and transmission capacities

The Nordic electricity market experienced extremely high prices during the winter 2009/2010. Using real data from the peak price hours the zonal solution from the Nordic market is replicated and compared to the nodal price solution when the central grid and its physical characteristics are explicitly modelled. Demand elasticity is introduced to the bid curves and its effect on prices and network utilisation is studied for the nodal solution. The sensitivity of the zonal solution to the changes in aggregate transfer capacities is investigated. The results demonstrate that better system utilisation is possible without capacity expansion. Nodal pricing solutions compared to the actual zonal pricing mechanism give insights into how the system functions in strained capacity situations and what hinders a more efficient system utilisation

Simulation of congestion management and security constraints in the Nordic electricity market

Presently in the Nordic day-ahead market, zonal pricing or market splitting is used for relieving congestion between a predetermined set of price areas. Constraints internal to the price areas are resolved by counter trading or redispatching in the regulation market. In a model of the Nordic electricity market we consider an hourly case from winter 2010 and present analyses of the effects of different congestion management methods on prices, quantities, surpluses and network utilization. We also study the effects of two different ways of taking into account security constraints

A Nodal Pricing Model for the Nordic Electricity Market

In the Nordic day-ahead electricity market zonal pricing or market splitting is used for relieving congestion between a predetermined set of bidding areas. This congestion management method represents an aggregation of individual connection points into bidding areas, and flows from the actual electricity network are only partly represented in the market clearing. Because of several strained situations in the power system during 2009 and 2010, changes in the congestion management method have been considered by the Norwegian regulator. In this paper we discuss nodal pricing in the Nordic power market, and compare it to optimal and simplified zonal pricing, the latter being used in today’s market. A model of the Nordic electricity market is presented together with a discussion of the calibration of actual market data for four hourly case studies with different load and import/exports to the Nordic area. The market clearing optimization model incorporates thermal and security flow constraints. We analyze the effects on prices and grid constraints and quantify the benefits and inefficiencies of the different methods. We find that the price changes with nodal pricing may not be dramatic, although in cases where intra-zonal constraints are badly represented by the aggregate transfer capacities in the simplified zonal model the nodal prices may be considerably higher on average and vary more than the simplified zonal prices. On the other hand nodal prices may vary less than the simplified zonal prices if aggregate transfer capacities are set too tightly. Allowing for more prices in the Nordic power market would make dealing with capacity limits easier and more transparent