scholarly journals Optimal Pump Scheduling for Urban Drainage under Variable Flow Conditions

Resources ◽  
2018 ◽  
Vol 7 (4) ◽  
pp. 73 ◽  
Author(s):  
Oreste Fecarotta ◽  
Armando Carravetta ◽  
Maria Morani ◽  
Roberta Padulano
Keyword(s):  
Power Efficiency ◽  
Drainage System ◽  
Mixed Integer ◽  
Urban Drainage ◽  
Integer Optimization ◽  
Average Value ◽  
Computational Performance ◽  
Set Up ◽  
Mixed Integer Optimization Model ◽  
Inflow Discharge

The paper is focused on the optimal scheduling of a drainage pumping station, complying with variations in the pump rotational speed and a recurrent pattern for the inflow discharge. The paper is structured in several consecutive steps. In the first step, the experimental set-up is described and results of calibration tests on different pumping machines are presented to obtain equations linking significant variables (discharge, head, power, efficiency). Then, those equations are utilized to build a mixed-integer optimization model able to find the scheduling solution that minimizes required pumping energy. The model is solved with respect to a case study referred to a urban drainage system in Naples (Italy) and optimization results are analysed to provide insights on the algorithm computational performance and on the influence of pumping machine characteristics on the overall efficiency savings. With reference to the simulated scenarios, an average value of 32% energy can be saved with an optimized control. Its actual value depends on the hydraulic characteristics of the system.

An analytical approach for fantasy football draft and lineup management

2016 ◽  
Vol 12 (1) ◽  
Author(s):  
Adrian Becker ◽  
Xu Andy Sun
Keyword(s):  
National Football League ◽  
Mixed Integer ◽  
Trade Association ◽  
Optimization Strategy ◽  
Integer Optimization ◽  
Fantasy Sports ◽  
Fantasy Football ◽  
The Rich ◽  
Set Up ◽  
Mixed Integer Optimization Model

AbstractIn this paper, we consider fantasy football, an increasingly-popular online game based on the actual, on-the-field performances of players in the National Football League. It is estimated by the Fantasy Sports Trade Association that in 2011 there were 35 million people in the US and Canada playing fantasy sports online. About 85 percent of all fantasy sports participants play fantasy football, most of whom have their games set up in major media websites such as Yahoo!, ESPN, MSN, and NFL. Numerous websites specialize in reporting NFL games, providing preseason rankings, fantasy points projections, team and player statistics, and expert draft opinions. However, despite the vast popularity of the game, the intensive analysis by experts, and various online tools that offer prediction for the values of players, to the best of our knowledge, there is no method that provides a comprehensive optimization strategy for the entire Fantasy Football season. We set out to develop such a methodology that predicts team and player performance based on the rich historical data, and builds a mixed-integer optimization model using such predictions for the draft selection as well as weekly line-up management that incorporates the entire objective of winning a fantasy football season. Numerical tests of our model show promising performance.

scholarly journals Benchmarks for Current Linear and Mixed Integer Optimization Solvers

2015 ◽  
Vol 63 (6) ◽  
pp. 1923-1928 ◽  
Author(s):  
Josef Jablonský
Keyword(s):  
Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Large Scale ◽  
Optimization Problems ◽  
Academic Research ◽  
Mixed Integer ◽  
Important Class ◽  
Integer Optimization ◽  
Computational Performance ◽  
Optimization Solvers

Linear programming (LP) and mixed integer linear programming (MILP) problems belong among very important class of problems that find their applications in various managerial consequences. The aim of the paper is to discuss computational performance of current optimization packages for solving large scale LP and MILP optimization problems. Current market with LP and MILP solvers is quite extensive. Probably among the most powerful solvers GUROBI 6.0, IBM ILOG CPLEX 12.6.1, and XPRESS Optimizer 27.01 belong. Their attractiveness for academic research is given, except their computational performance, by their free availability for academic purposes. The solvers are tested on the set of selected problems from MIPLIB 2010 library that contains 361 test instances of different hardness (easy, hard, and not solved).

Optimization on Supply Chain Network Based on High-Tech Products Life Cycle

2013 ◽  
Vol 416-417 ◽  
pp. 1920-1925
Author(s):  
Lei Zhang ◽  
Yan Yan Kong
Keyword(s):  
Life Cycle ◽  
Profit Maximization ◽  
Transportation Cost ◽  
Pso Algorithm ◽  
Mixed Integer ◽  
High Tech ◽  
Integer Optimization ◽  
Time Model ◽  
Decision Variables ◽  
Mixed Integer Optimization Model

In view of the characteristics of market demands of high-tech products life cycle at all stages, the response time model of the products life cycle at all stages was established according to the differences of products stage response points. Based on this, the production cost/time, transportation cost/time, shortage cost, sales price, and other factors of the products life cycle at all stages were taken into consideration. The 0-1 mixed integer optimization model of multi-factory and multi-distribution center with profit maximization as the optimization objective was established. Particle Swarm Optimization (PSO) algorithm was used to solve the decision variables. Finally, a numerical example was used to illustrate the practical application value of this model.

scholarly journals Recent Advancements in Commercial Integer Optimization Solvers for Business Intelligence Applications

2021 ◽  
Author(s):  
Cheng Seong Khor
Keyword(s):  
Business Intelligence ◽  
Mixed Integer Linear Programming ◽  
Branch And Cut ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Integer Optimization ◽  
Computational Performance ◽  
Solution Methods ◽  
Future Work ◽  
Optimization Solvers

The chapter focuses on the recent advancements in commercial integer optimization solvers as exemplified by the CPLEX software package particularly but not limited to mixed-integer linear programming (MILP) models applied to business intelligence applications. We provide background on the main underlying algorithmic method of branch-and-cut, which is based on the established optimization solution methods of branch-and-bound and cutting planes. The chapter also covers heuristic-based algorithms, which include preprocessing and probing strategies as well as the more advanced methods of local or neighborhood search for polishing solutions toward enhanced use in practical settings. Emphasis is given to both theory and implementation of the methods available. Other considerations are offered on parallelization, solution pools, and tuning tools, culminating with some concluding remarks on computational performance vis-à-vis business intelligence applications with a view toward perspective for future work in this area.

Towards the Implementation of Optimal Train Loading Plan in the Athens-Thessaloniki Freight Services

2017 ◽  
Vol 8 (3) ◽  
pp. 39-53
Author(s):  
Athanasios Ballis ◽  
Fillipos Karapetis ◽  
Theocharis Ballis
Keyword(s):  
Information System ◽  
Daily Basis ◽  
Operating Conditions ◽  
Mixed Integer ◽  
Integer Optimization ◽  
Container Transport ◽  
Railway Infrastructure ◽  
Mixed Integer Optimization Model ◽  
Pragmatic Aspects ◽  
Train Loading

The main goal of train loading optimization is the proper assignment of loading units onto the wagons, taking under consideration numerous factors like the maximum axle load restrictions, the condition of the railway infrastructure, the operating conditions, safety regulations etc. The typical expression of the problem is usually formulated under one of the two following assumptions: (a) the commodity load is predefined or (b) the number and type of wagons is fixed. The current work describes the steps that were followed and enabled the analysis, optimization and integration of the train loading plan into the information system that supports the new railway service of TRAINOSE for containers transport on the Athens – Thessaloniki line. This new service, named iCS, was launched in December 2013 and ever since operates on a daily basis. The work includes a literature review, a mention of the pragmatic aspects that influence container transport and train loading plan, the presentation of the heuristic which is implemented in the information system of iCS service, a validation process against a mixed integer optimization model and finally concludes with the proposed solution for the iCS wagon loading problem.

An optimization model for selecting wood supply contracts

2020 ◽  
Vol 50 (4) ◽  
pp. 399-412 ◽  
Author(s):  
Ali Rahimi ◽  
Mikael Rönnqvist ◽  
Luc LeBel ◽  
Jean-François Audy
Keyword(s):  
Optimization Model ◽  
Wood Fiber ◽  
Pulp And Paper ◽  
Raw Material ◽  
Mixed Integer ◽  
Integer Optimization ◽  
Paper Mills ◽  
Wood Supply ◽  
Portfolio Strategies ◽  
Mixed Integer Optimization Model

Procurement for forest companies with pulp and paper mills aims to ensure that a sufficient volume of wood supply enters the production process. Numerous suppliers and contract types are available; however, their selection is a complex decision for procurement managers. In addition, managers typically dedicate a portion of their wood fiber demand to each group of suppliers, which is referred to as a portfolio strategy. Despite the available literature in contract selection, the consideration of contract types and their characteristics have not been addressed for the complex procurement process. In this study, a mixed-integer optimization model is proposed to best select contracts for pulp and paper procurement. The challenge was to plan deliveries in each time period to satisfy the demand of raw material at the mills. The potential of this model is demonstrated with a case study based on characteristics from a forest company in Quebec, Canada. A comparison between traditional fixed and flexible contracts is presented. Different portfolio strategies are also evaluated for groups of suppliers to investigate potential improvements.

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