scholarly journals An Optimization Approach to the Low-Frequency Entire Train Formation at the Loading Area

2019 ◽  
Vol 11 (19) ◽  
pp. 5500
Author(s):  
Lin ◽  
Yang ◽  
Zuo ◽  
Liu ◽  
Zhao ◽  
...  
Keyword(s):  
Programming Model ◽  
Low Frequency ◽  
Transportation Systems ◽  
Optimal Operation ◽  
Optimization Approach ◽  
Inventory Cost ◽  
Eoq Model ◽  
Railway Industry ◽  
Pros And Cons ◽  
Using Data

It is well known that the shift of transporting bulk cargo from roads to railways is an important measure to reduce carbon emissions of the overall transportation systems. In order to increase the attractiveness of railway transport, companies usually provide some discounts to the customers with great transport demand so that entire trains can be operated. Since the operation of entire trains can reduce the reclassification times of shipments, the expenses of railway operations can be reduced. However, when the volume of shipment is not sufficient, the door-to-door direct transportation (in the railway industry specifically, “door-to-door” means running trains from supplier’s warehouse to customer’s warehouse) of the entire train often leads to a decrease in the frequency of delivery, which increases the average stock of users, thus increasing the inventory cost of users. Therefore, how to balance the pros and cons of the two is exactly the problem to be studied. In this paper, the optimal operation plan is obtained by minimizing the total cost of the stockholding of suppliers and customers, as well as the transportation costs of an entire train and non-direct train. Based on the classic economic order quantity (EOQ) model, a 0-1 integer programming model with the constraint of the maximum stock level is proposed to solve this problem. And an innovative approach is used to calculate the actual average stock of the customer. Finally, the model is validated and its effectiveness is confirmed using a real-world case, which is carried out using data from the China rail system.

scholarly journals Model Penentuan Lot Pemesanan Dengan Mempertimbangkan Unit Diskon dan Batasan Kapasitas Gudang dengan Program Dinamis

2017 ◽  
Vol 18 (1) ◽  
pp. 94 ◽  
Author(s):  
Dana Marsetiya Utama
Keyword(s):  
Dynamic Programming ◽  
Programming Model ◽  
Classical Model ◽  
Dynamic Program ◽  
Lot Size ◽  
Inventory Cost ◽  
Inventory Costs ◽  
Eoq Model ◽  
Total Inventory ◽  
The Cost

The classical model of dynamic programming in determining the economical lot size  of orders generally considers the cost of orders and inventory costs. However, firms are often confronted with the situation of determining the number of economic orders if the seller gives incremental discounts to the buyer and limits the warehouse capacity. In this paper, explains the model of determining lot order by considering discount and limitation of warehouse capacity with dynamic program. The dynamic program model is compared with the Economic Order Quantity (EOQ) model considering the discount and the limitation of warehouse capacity. The comparison result shows that dynamic programming model can minimize total inventory cost compared to EOQ.

scholarly journals A robust-heuristic optimization approach to a green supply chain design with consideration of assorted vehicle types and carbon policies under uncertainty

2021 ◽  
Author(s):  
Zahra Homayouni ◽  
Mir Saman Pishvaee ◽  
Hamed Jahani ◽  
Dmitry Ivanov
Keyword(s):  
Supply Chains ◽  
Large Scale ◽  
Programming Model ◽  
Supply Chain Design ◽  
Heuristic Optimization ◽  
Optimization Approach ◽  
Economic Uncertainty ◽  
Cap And Trade ◽  
Sustainable Logistics ◽  
Goal Programming Model

AbstractAdoption of carbon regulation mechanisms facilitates an evolution toward green and sustainable supply chains followed by an increased complexity. Through the development and usage of a multi-choice goal programming model solved by an improved algorithm, this article investigates sustainability strategies for carbon regulations mechanisms. We first propose a sustainable logistics model that considers assorted vehicle types and gas emissions involved with product transportation. We then construct a bi-objective model that minimizes total cost as the first objective function and follows environmental considerations in the second one. With our novel robust-heuristic optimization approach, we seek to support the decision-makers in comparison and selection of carbon emission policies in supply chains in complex settings with assorted vehicle types, demand and economic uncertainty. We deploy our model in a case-study to evaluate and analyse two carbon reduction policies, i.e., carbon-tax and cap-and-trade policies. The results demonstrate that our robust-heuristic methodology can efficiently deal with demand and economic uncertainty, especially in large-scale problems. Our findings suggest that governmental incentives for a cap-and-trade policy would be more effective for supply chains in lowering pollution by investing in cleaner technologies and adopting greener practices.

Optimal operation of alumina proportioning and mixing process based on stochastic optimization approach

2021 ◽  
Vol 113 ◽  
pp. 104855
Author(s):  
Yanyan Yin ◽  
Lingshuang Kong ◽  
Chunhua Yang ◽  
Weihua Gui ◽  
Fei Liu ◽  
...  
Keyword(s):  
Stochastic Optimization ◽  
Optimal Operation ◽  
Optimization Approach ◽  
Mixing Process

Concorrenza e regolazione nel settore ferroviario: l'importanza del materiale rotabile

2009 ◽  
pp. 47-72
Author(s):  
Carlo Cambini
Keyword(s):  
Jel Classification ◽  
Railway Transport ◽  
Transport Regulation ◽  
Market Competitiveness ◽  
Railway Industry ◽  
Pros And Cons ◽  
Overall Efficiency ◽  
Barrier To Entry ◽  
The Uk

- The liberalization process in the railway industry is highly influenced by the availability of rolling stocks. Although these assets are duplicable and cannot therefore be defined as essential facilities, evidence from many countries shows that they represent the most relevant barrier to entry in the market. In this paper, following the UK experience, we analyse the role of the rolling stocks and the hypothesis of a vertical separation of these assets from the present owner, i.e. the incumbent operator Trenitalia SpA. We therefore evaluate the pros and cons of a potential de-integration of the Italian railway industry in order to enhance market competitiveness and the overall efficiency of this industry. . Keywords: railway transport, regulation, competition, essential facilities Parole chiave: trasporto ferroviario, regolazione, concorrenza, asset essenziali . Jel Classification: L43 - L51 - L92

Design of hydrogen supply chains under demand uncertainty – a case study of passenger transport in Germany

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Anton Ochoa Bique ◽  
Leonardo K. K. Maia ◽  
Ignacio E. Grossmann ◽  
Edwin Zondervan
Keyword(s):  
Stochastic Optimization ◽  
Demand Uncertainty ◽  
Programming Model ◽  
Cost Minimization ◽  
Water Electrolysis ◽  
Scenario Tree ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Strong Impact ◽  
Hydrogen Supply

Abstract A strategy for the design of a hydrogen supply chain (HSC) network in Germany incorporating the uncertainty in the hydrogen demand is proposed. Based on univariate sensitivity analysis, uncertainty in hydrogen demand has a very strong impact on the overall system costs. Therefore we consider a scenario tree for a stochastic mixed integer linear programming model that incorporates the uncertainty in the hydrogen demand. The model consists of two configurations, which are analyzed and compared to each other according to production types: water electrolysis versus steam methane reforming. Each configuration has a cost minimization target. The concept of value of stochastic solution (VSS) is used to evaluate the stochastic optimization results and compare them to their deterministic counterpart. The VSS of each configuration shows significant benefits of a stochastic optimization approach for the model presented in this study, corresponding up to 26% of infrastructure investments savings.

scholarly journals Analysis of a Stochastic Programming Model for Optimal Hydropower System Operation under a Deregulated Electricity Market by Considering Forecasting Uncertainty

Water ◽  
2018 ◽  
Vol 10 (7) ◽  
pp. 885 ◽  
Author(s):  
Bin Xu ◽  
Ping-An Zhong ◽  
Baoyi Du ◽  
Juan Chen ◽  
Weifeng Liu ◽  
...  
Keyword(s):  
Stochastic Programming ◽  
Electricity Market ◽  
Energy Production ◽  
Programming Model ◽  
Optimal Operation ◽  
Spot Price ◽  
Deregulated Electricity Market ◽  
Hydropower System ◽  
Stochastic Programming Model ◽  
Hydropower Operation

In a deregulated electricity market, optimal hydropower operation should be achieved through informed decisions to facilitate the delivery of energy production in forward markets and energy purchase level from other power producers within real-time markets. This study develops a stochastic programming model that considers the influence of uncertain streamflow on hydropower energy production and the effect of variable spot energy prices on the cost of energy purchase (energy shortfall). The proposed model is able to handle uncertainties expressed by both a probability distribution and discretized scenarios. Conflicting decisions are resolved by maximizing the expected value of net revenue, which jointly considers benefit and cost terms under uncertainty. Methodologies are verified using a case study of the Three Gorges cascade hydropower system. The results demonstrate that optimal operation policies are derived based upon systematic evaluations on the benefit and cost terms that are affected by multiple uncertainties. Moreover, near-optimal operation policy under the case of inaccurate spot price forecasts is also analyzed. The results also show that a proper policy for guiding hydropower operation seeks the best compromise between energy production and energy purchase levels, which explores their nonlinear tradeoffs over different time periods.

Maximizing the value for money of road projects through digitalization

2018 ◽  
Vol 19 (1-2) ◽  
pp. 69-92 ◽  
Author(s):  
Carlos Oliveira Cruz ◽  
Joaquim Miranda Sarmento
Keyword(s):  
Autonomous Vehicles ◽  
Technological Development ◽  
Central Element ◽  
Transportation Systems ◽  
The Road ◽  
Road Systems ◽  
Technological Developments ◽  
Road Projects ◽  
Barriers To Implementation ◽  
Using Data

Roads are a central element of transportation systems, enabling economic and social development, fostering territorial cohesion and facilitating the movement of people and cargo. Governments have devoted significant financial resources to developing and improving their road networks, and are still facing increasing pressure to ensure proper maintenance and payments to those concessionaires that developed roads under public–private partnership arrangements. As in other sectors, digitalization is paving a way towards significant changes in the way we build, operate and finance infrastructure. These changes will have a profound impact on the entire life cycle of an infrastructure, from the design and/or construction stage, to its operation and transfer. This article provides an overall overview of the main technological developments which are, or could impact road infrastructure in the short, medium and long term. For each technological development identified in our research, we analyse the potential impact on Capex, Opex and revenues as well as their level of maturity and expected lifetime for mass adoption, and also the main bottlenecks or barriers to implementation. Additionally, we explore potential savings on investment (capex) and operational costs (opex) and increase in revenues, using data from the Portuguese highway companies. Savings can represent almost 30% of capex and opex. Overall, savings and increases in revenues can represent an impact similar to 20–40% of current revenues. The findings show that digitalization and technological development in the road sector can significantly impact the economic performance of roads, thus enhancing the value of money for the society. The findings also show that there might be some excess capacity of road systems once autonomous vehicles achieve higher market penetration. However, there are still some relevant legal, regulatory, institutional and technological and economic barriers that are slowing down the digitalization process.

Numerical Study on Hydrodynamic Responses of a Two-Body System in Side-by-Side Operation

2016 ◽  
Author(s):  
Shaowu Ou ◽  
Shixiao Fu ◽  
Wei Wei ◽  
Tao Peng ◽  
Xuefeng Wang
Keyword(s):  
Numerical Study ◽  
Low Frequency ◽  
Optimal Operation ◽  
Hydrodynamic Interactions ◽  
Irregular Waves ◽  
Mooring System ◽  
Time Varying ◽  
Body System ◽  
The Time Domain ◽  
Two Bodies

Typically, in some side-by-side offshore operations, the speed of vessels is very low or even 0 and the headings are manually maneuvered. In this paper, the hydrodynamic responses of a two-body system in such operations under irregular seas are investigated. The numerical model includes two identical PSVs (Platform Supply Vessel) as well as the fenders and connection lines between them. A horizontal mooring system constraining the low frequency motions is set on one of the ships to simulate maneuver system. Accounting for the hydrodynamic interactions between two bodies, 3D potential theory is applied for the analysis of their hydrodynamic coefficients. With wind and current effects included, these coefficients are further applied in the time domain simulations in irregular waves. The relevant coefficients are estimated by experiential formulas. Time-varying loads on fenders and connection lines are analyzed. Meanwhile, the relative motions as well as the effects of the hydrodynamic interactions between ships are further discussed, and finally an optimal operation scheme in which operation can be safely performed is summarized.

scholarly journals Computer Assisted Localization of a Heart Arrhythmia

2018 ◽  
Author(s):  
Chris Vogl ◽  
Peng Zheng ◽  
Stephen P. Seslar ◽  
Aleksandr Y. Aravkin
Keyword(s):  
Diagnostic Procedure ◽  
Feasibility Problem ◽  
Computer Assisted ◽  
Optimization Approach ◽  
Arrival Times ◽  
Heart Arrhythmia ◽  
Simulation Based ◽  
Heart Anatomy ◽  
Using Data ◽  
Diagnostic Catheter

AbstractWe consider the problem of locating a point-source heart arrhythmia using data from a standard diagnostic procedure, where a reference catheter is placed in the heart, and arrival times from a second diagnostic catheter are recorded as the diagnostic catheter moves around within the heart.We model this situation as a nonconvex feasibility problem, where given a set of arrival times, we look for a source location that is consistent with the available data. We develop a new optimization approach and fast algorithm to obtain online proposals for the next location to suggest to the operator as she collects data. We validate the procedure using a Monte Carlo simulation based on patients’ electrophysiological data. The proposed procedure robustly and quickly locates the source of arrhythmias without any prior knowledge of heart anatomy.

scholarly journals Evaluating the potential trade-off between students’ satisfaction and school performance using evolutionary multiobjective optimization

2020 ◽  
Author(s):  
Oscar D. Marcenaro-Gutierrez ◽  
Sandra Gonzalez-Gallardo ◽  
Mariano Luque
Keyword(s):  
Academic Performance ◽  
High Performance ◽  
Multiobjective Programming ◽  
Programming Model ◽  
Objective Functions ◽  
Explanatory Variables ◽  
Multiobjective Analysis ◽  
Using Data ◽  
Teaching Learning ◽  
Students Satisfaction

In this article, we carry out a combined econometric and multiobjective analysis using data from a representative sample of Andalusian schools. In particular, four econometric models are estimated in which the students’ academic performance (scores in math and reading, and percentage of students reaching a certain threshold in both subjects, respectively) are regressed against the satisfaction of students with different aspects of the teaching-learning process. From these estimates, four objective functions are defined which have been simultaneously maximized, subject to a set of constraints obtained by analyzing dependencies between explanatory variables. This multiobjective programming model is intended to optimize the students’ academic performance as a function of the students’ satisfaction. To solve this problem we use a decomposition-based evolutionary multiobjective algorithm called Global WASF-GA with different scalarizing functions which allows generating an approximation of the Pareto optimal front. In general, the results show the importance of promoting respect and closer interaction between students and teachers, as a way to increase the average performance of the students and the proportion of high performance students.

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