Integrated Scheduling for a Multi-Product Pipeline Network With Delivery Due Dates

2018 ◽  
Author(s):  
Ning Xu ◽  
Qi Liao ◽  
Yongtu Liang ◽  
Zhengbing Li ◽  
Haoran Zhang
Keyword(s):  
Time Horizon ◽  
Large Scale ◽  
Mixed Integer ◽  
Market Demand ◽  
Due Dates ◽  
Long Distance ◽  
Decomposition Approach ◽  
Pipeline Network ◽  
Integrated Scheduling ◽  
Product Pipeline

Currently, pipeline is the most effective way to transport large-volume products over long distance. To effectively satisfy market demands for multiple refined products by delivery due dates, the multi-product pipeline network usually transports several refined products in sequence from refineries to certain destinations. The integrated scheduling of multi-product pipeline network, including inventory management, transport routes planning, batch sequence, batch volume, et al., is one of the most strategic problems due to its large-scale, complexity as well as economic significance. This subject has been widely studied during the last decade. However, most researches focus on large-size scheduling models whose computational efficiency greatly decreases for a complex pipeline network or a long time horizon. Aiming at this problem, the paper develops an efficient decomposition approach, which is composed of two mixed integer linear programming (MILP) models. The first model divides the entire time horizon into several intervals according to delivery due dates and optimizes the transport routes and total transport volume during each interval with considering market demand, production campaigns and inventory limits. Then the solved results are used by the second model which sets the objective function as the membership function based on fuzzy delivery due dates. Besides, a series of operational constraints are also considered in the second model to obtain the optimal batch sequence, batch volume, delivery volume and delivery time in each node. Finally, the proposed approach is applied to a Chinese real-world pipeline network that includes 5 complex multi-product pipelines associated with 6 refineries and 2 depots. The results demonstrate that the proposed approach can provide a guideline for long-term pipeline network scheduling with delivery due dates.

scholarly journals A Redesigned Benders Decomposition Approach for Large-Scale In-Transit Freight Consolidation Operations

2018 ◽  
Vol 11 (2) ◽  
pp. 1-15 ◽  
Author(s):  
Abdulkader S. Hanbazazah ◽  
Luis E. Abril ◽  
Nazrul I. Shaikh ◽  
Murat Erkoc
Keyword(s):  
Large Scale ◽  
Benders Decomposition ◽  
Scale Up ◽  
Third Party ◽  
Mixed Integer ◽  
Continuous Variables ◽  
Due Dates ◽  
Decomposition Approach ◽  
Freight Consolidation ◽  
In Transit

The growth in online shopping and third-party logistics has caused a revival of interest in finding optimal solutions to the large-scale, in-transit freight consolidation problem. Given the shipment date, size, origin, destination, and due dates of multiple shipments distributed over space and time, the problem requires determining when to consolidate some of these shipments into one shipment at an intermediate consolidation point so as to minimize shipping costs while satisfying the due date constraints. In this article, the authors develop a mixed-integer programming formulation for a multi-period freight consolidation problem that involves multiple products, suppliers, and potential consolidation points. Benders decomposition is then used to replace a large number of integer freight-consolidation variables by a small number of continuous variables that reduce the size of the problem without impacting optimality. The results show that Benders decomposition provides a significant scale-up in the performance of the solver. The authors demonstrate their approach using a large-scale case with more than 27.5 million variables and 9.2 million constraints.

A Novel Approach for Two-Stage UAV Path Planning in Pipeline Network Inspection

2020 ◽  
Author(s):  
Rui Qiu ◽  
Yongtu Liang
Keyword(s):  
Path Planning ◽  
Large Scale ◽  
Flight Path ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Two Stage ◽  
Calculation Time ◽  
Pipeline Network ◽  
Second Stage ◽  
Computational Performance

Abstract Currently, unmanned aerial vehicle (UAV) provides the possibility of comprehensive coverage and multi-dimensional visualization of pipeline monitoring. Encouraged by industry policy, research on UAV path planning in pipeline network inspection has emerged. The difficulties of this issue lie in strict operational requirements, variable flight missions, as well as unified optimization for UAV deployment and real-time path planning. Meanwhile, the intricate structure and large scale of the pipeline network further complicate this issue. At present, there is still room to improve the practicality and applicability of the mathematical model and solution strategy. Aiming at this problem, this paper proposes a novel two-stage optimization approach for UAV path planning in pipeline network inspection. The first stage is conventional pre-flight planning, where the requirement for optimality is higher than calculation time. Therefore, a mixed integer linear programming (MILP) model is established and solved by the commercial solver to obtain the optimal UAV number, take-off location and detailed flight path. The second stage is re-planning during the flight, taking into account frequent pipeline accidents (e.g. leaks and cracks). In this stage, the flight path must be timely rescheduled to identify specific hazardous locations. Thus, the requirement for calculation time is higher than optimality and the genetic algorithm is used for solution to satisfy the timeliness of decision-making. Finally, the proposed method is applied to the UAV inspection of a branched oil and gas transmission pipeline network with 36 nodes and the results are analyzed in detail in terms of computational performance. In the first stage, compared to manpower inspection, the total cost and time of UAV inspection is decreased by 54% and 56% respectively. In the second stage, it takes less than 1 minute to obtain a suboptimal solution, verifying the applicability and superiority of the method.

Optimal Configuration Design of Gas Turbine Cogeneration Plants by a MILP Decomposition Approach

2007 ◽  
Author(s):  
Ryohei Yokoyama
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Large Scale ◽  
Numerical Study ◽  
Optimal Configuration ◽  
Mixed Integer ◽  
Configuration Design ◽  
Design Problems ◽  
Decomposition Approach ◽  
Energy Demands

To attain the highest economic and energy saving characteristics of gas turbine cogeneration plants, it is necessary to rationally determine capacities and numbers of gas turbines and auxiliary equipment in consideration of their operational strategies corresponding to seasonal and hourly variations in energy demands. Some optimization approaches based on the mixed-integer linear programming (MILP) have been proposed to such configuration design problems of energy supply plants. However, with increases in the numbers of the equipment which must be considered as candidates as well as the periods which must be set for variations in energy demands, the optimal configuration design problems become too large-scale and complex to solve. The author has proposed a MILP decomposition approach to obtain quasi-optimal solutions of the optimal configuration design problems in reasonable computation times. However, this approach has been limited to the optimal configuration design problems where equipment capacities are treated continuously. In this paper, the MILP decomposition approach is extended to the optimal configuration design problems where equipment capacities are treated discretely. The effectiveness of this extended approach is investigated through a numerical study on a gas turbine cogeneration plant.

The Use of Decomposition for the Large Scale Synthesis/Design Optimization of Highly Coupled, Highly Dynamic Energy Systems: Part II—Applications

2000 ◽  
Author(s):  
Jules R. Muñoz ◽  
Michael R. von Spakovsky
Keyword(s):  
Global Convergence ◽  
Design Optimization ◽  
Large Scale ◽  
Environmental Control ◽  
Linear Optimization ◽  
Mixed Integer ◽  
Decomposition Approach ◽  
Independent Variables ◽  
Synthesis Design ◽  
Non Linear

Abstract An application of the Iterative Local-Global Optimization (ILGO) decomposition approach developed in an accompanying paper (Muñoz and von Spakovsky, 2000b) is presented. The synthesis / design optimization of a turbofan engine coupled to an environmental control system for a military aircraft was carried out. The problem was solved for a given mission (i.e. the load / environmental profile) composed of fifteen segments. The number of decision (independent) variables used for this highly non-linear optimization problem is one hundred fifty-three, some of which are integer. Both thermodynamic and physical (weight and volume) simulations use state-of-the art tools. Two objective functions were investigated: take-off gross weight and mission fuel consumption, and no observable differences were found in the final results. In addition to the mathematical foundations for global convergence of the proposed decomposition approach presented in Muñoz and von Spakovsky (2000b), numerical support for this convergence was found by solving the entire mixed-integer non-linear programming (MINLP) problem without decomposition using a subset of the independent variables. The constant value of the marginal costs (or linear behavior of the Optimum Response Surface — OSR) played a major role in the global convergence of the ILGO.

Optimal Test Assembly in Practice

2013 ◽  
Vol 221 (3) ◽  
pp. 190-200 ◽  
Author(s):  
Jörg-Tobias Kuhn ◽  
Thomas Kiefer
Keyword(s):  
Particle Physics ◽  
Large Scale ◽  
Block Design ◽  
Linear Optimization ◽  
Mixed Integer ◽  
Optimal Test ◽  
Automated Test Assembly ◽  
Test Assembly ◽  
Block Level ◽  
Mixed Integer Linear Optimization

Several techniques have been developed in recent years to generate optimal large-scale assessments (LSAs) of student achievement. These techniques often represent a blend of procedures from such diverse fields as experimental design, combinatorial optimization, particle physics, or neural networks. However, despite the theoretical advances in the field, there still exists a surprising scarcity of well-documented test designs in which all factors that have guided design decisions are explicitly and clearly communicated. This paper therefore has two goals. First, a brief summary of relevant key terms, as well as experimental designs and automated test assembly routines in LSA, is given. Second, conceptual and methodological steps in designing the assessment of the Austrian educational standards in mathematics are described in detail. The test design was generated using a two-step procedure, starting at the item block level and continuing at the item level. Initially, a partially balanced incomplete item block design was generated using simulated annealing, whereas in a second step, items were assigned to the item blocks using mixed-integer linear optimization in combination with a shadow-test approach.

Going the Distance

2020 ◽  
Author(s):  
Ron Harris
Keyword(s):  
Large Scale ◽  
Western Europe ◽  
Family Firms ◽  
Global Trade ◽  
Long Distance ◽  
Business Corporation ◽  
Modern Economy ◽  
Key Factor ◽  
Silk Route ◽  
Passive Investors

Before the seventeenth century, trade across Eurasia was mostly conducted in short segments along the Silk Route and Indian Ocean. Business was organized in family firms, merchant networks, and state-owned enterprises, and dominated by Chinese, Indian, and Arabic traders. However, around 1600 the first two joint-stock corporations, the English and Dutch East India Companies, were established. This book tells the story of overland and maritime trade without Europeans, of European Cape Route trade without corporations, and of how new, large-scale, and impersonal organizations arose in Europe to control long-distance trade for more than three centuries. It shows that by 1700, the scene and methods for global trade had dramatically changed: Dutch and English merchants shepherded goods directly from China and India to northwestern Europe. To understand this transformation, the book compares the organizational forms used in four major regions: China, India, the Middle East, and Western Europe. The English and Dutch were the last to leap into Eurasian trade, and they innovated in order to compete. They raised capital from passive investors through impersonal stock markets and their joint-stock corporations deployed more capital, ships, and agents to deliver goods from their origins to consumers. The book explores the history behind a cornerstone of the modern economy, and how this organizational revolution contributed to the formation of global trade and the creation of the business corporation as a key factor in Europe's economic rise.

scholarly journals Future Power Train Solutions for Long-Haul Trucks

2021 ◽  
Vol 13 (4) ◽  
pp. 2225
Author(s):  
Ralf Peters ◽  
Janos Lucian Breuer ◽  
Maximilian Decker ◽  
Thomas Grube ◽  
Martin Robinius ◽  
...  
Keyword(s):  
Fuel Cells ◽  
Co2 Emissions ◽  
Value Chain ◽  
Large Scale ◽  
New Technology ◽  
Co2 Reduction ◽  
Road Transport ◽  
Transport Sector ◽  
Long Distance ◽  
Production Of Hydrogen

Achieving the CO2 reduction targets for 2050 requires extensive measures being undertaken in all sectors. In contrast to energy generation, the transport sector has not yet been able to achieve a substantive reduction in CO2 emissions. Measures for the ever more pressing reduction in CO2 emissions from transportation include the increased use of electric vehicles powered by batteries or fuel cells. The use of fuel cells requires the production of hydrogen and the establishment of a corresponding hydrogen production system and associated infrastructure. Synthetic fuels made using carbon dioxide and sustainably-produced hydrogen can be used in the existing infrastructure and will reach the extant vehicle fleet in the medium term. All three options require a major expansion of the generation capacities for renewable electricity. Moreover, various options for road freight transport with light duty vehicles (LDVs) and heavy duty vehicles (HDVs) are analyzed and compared. In addition to efficiency throughout the entire value chain, well-to-wheel efficiency and also other aspects play an important role in this comparison. These include: (a) the possibility of large-scale energy storage in the sense of so-called ‘sector coupling’, which is offered only by hydrogen and synthetic energy sources; (b) the use of the existing fueling station infrastructure and the applicability of the new technology on the existing fleet; (c) fulfilling the power and range requirements of the long-distance road transport.

scholarly journals Allocation and Scheduling of Handling Resources in the Railway Container Terminal Based on Crossing Crane Area

2021 ◽  
Vol 13 (3) ◽  
pp. 1190
Author(s):  
Gang Ren ◽  
Xiaohan Wang ◽  
Jiaxin Cai ◽  
Shujuan Guo
Keyword(s):  
Programming Model ◽  
Container Terminal ◽  
Simultaneous Optimization ◽  
Mixed Integer ◽  
Gantry Crane ◽  
Optimization Scheme ◽  
Long Distance ◽  
Proposed Model ◽  
Hybrid Heuristic Algorithm ◽  
Searching Ability

The integrated allocation and scheduling of handling resources are crucial problems in the railway container terminal (RCT). We investigate the integrated optimization problem for handling resources of the crane area, dual-gantry crane (GC), and internal trucks (ITs). A creative handling scheme is proposed to reduce the long-distance, full-loaded movement of GCs by making use of the advantages of ITs. Based on this scheme, we propose a flexible crossing crane area to balance the workload of dual-GC. Decomposing the integrated problem into four sub-problems, a multi-objective mixed-integer programming model (MIP) is developed. By analyzing the characteristic of the integrated problem, a three-layer hybrid heuristic algorithm (TLHHA) incorporating heuristic rule (HR), elite co-evolution genetic algorithm (ECEGA), greedy rule (GR), and simulated annealing (SA) is designed for solving the problem. Numerical experiments were conducted to verify the effectiveness of the proposed model and algorithm. The results show that the proposed algorithm has excellent searching ability, and the simultaneous optimization scheme could ensure the requirements for efficiency, effectiveness, and energy-saving, as well as the balance rate of dual-GC.

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