scholarly journals Optimization of Queries with Conjunction of Predicates

2007 ◽  
Vol 2 (3) ◽  
pp. 288
Author(s):  
Nicoleta Liviana Tudor
Keyword(s):  
Optimization Algorithm ◽  
Cost Model ◽  
Dynamic Programming Algorithm ◽  
Heuristic Method ◽  
Programming Algorithm ◽  
Optimal Plan ◽  
Execution Plan ◽  
Rank Ordering ◽  
Optimal Linear ◽  
The Cost

<p>A method to optimize the access at the objects of a relational database is through the optimization of the queries. This article presents an approach of the cost model used in optimization of Select-Project-Join (SPJ) queries with conjunction of predicates and proposes a join optimization algorithm named System RO-H (System Rank Ordering Heuristic). The System RO-H algorithm for optimizing SPJ queries with conjunction of predicates is a System R Dynamic Programming algorithm that extends optimal linear join subplans using a rank-ordering heuristic method as follows: choosing a predicate in ascending order according to the h-metric, where the h-metric depends on the selectivity and the cost per tuple of the predicate, using an expression with heuristic constants.<br />The System Rank-Ordering Heuristic algorithm finds an optimal plan in the space of linear left deep join trees. The System RO-H algorithm saves not a single plan, but multiple optimal plans for every subset, one for each distinct such order, termed interesting order. In order to build an optimal execution plan for a set S of i relations, the optimal plan for each subset of S, consisting of i-1 relations is extended, using the Lemma based on a h-metric for predicates. Optimal plans for subsets are stored and reused. The optimization algorithm chooses a plan of least cost from the execution space.</p>

scholarly journals Profit Maximizing Control of a Microgrid with Renewable Generation and BESS Based on a Battery Cycle Life Model and Energy Price Forecasting

Energies ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 2904 ◽  
Author(s):  
Wenhao Zhuo ◽  
Andrey V. Savkin
Keyword(s):  
Dynamic Programming ◽  
Wind Farm ◽  
Optimization Problem ◽  
Cost Model ◽  
Dynamic Programming Algorithm ◽  
Operating Conditions ◽  
Programming Algorithm ◽  
Renewable Generation ◽  
The Cost ◽  
Charge Discharge

In this paper, an optimal control strategy is presented for grid-connected microgrids with renewable generation and battery energy storage systems (BESSs). In order to optimize the energy cost, the proposed approach utilizes predicted data on renewable power, electricity price, and load demand within a future period, and determines the appropriate actions of BESSs to control the actual power dispatched to the utility grid. We formulate the optimization problem as a Markov decision process and solve it with a dynamic programming algorithm under the receding horizon approach. The main contribution in this paper is a novel cost model of batteries derived from their life cycle model, which correlates the charge/discharge actions of batteries with the cost of battery life loss. Most cost models of batteries are constructed based on identifying charge–discharge cycles of batteries on different operating conditions, and the cycle counting methods used are analytical, so cannot be expressed mathematically and used in an optimization problem. As a result, the cost model proposed in this paper is a recursive and additive function over control steps that will be compatible with dynamic programming and can be included in the objective function. We test the proposed approach with actual data from a wind farm and an energy market operator.

scholarly journals Modeling Single-Picker Routing Problems in Classical and Modern Warehouses

2021 ◽  
Author(s):  
Dominik Goeke ◽  
Michael Schneider
Keyword(s):  
Dynamic Programming Algorithm ◽  
Practical Interest ◽  
Computational Effort ◽  
Programming Algorithm ◽  
Substantial Part ◽  
Routing Problem ◽  
Solution Approach ◽  
Compact Formulation ◽  
Single Block ◽  
The Cost

The standard single-picker routing problem (SPRP) seeks the cost-minimal tour to collect a set of given articles in a rectangular single-block warehouse with parallel picking aisles and a dedicated storage policy, that is, each stock-keeping unit is only available from one storage location in the warehouse. We present a compact formulation that forgoes classical subtour elimination constraints by directly exploiting two of the properties of an optimal picking tour used in the dynamic programming algorithm published in the seminal paper of Ratliff and Rosenthal. We extend the formulation to three important settings prevalent in modern e-commerce warehouses: scattered storage, decoupling of picker and cart, and multiple end depots. In numerical studies, our formulation outperforms existing standard SPRP formulations from the literature and proves able to solve large instances within short runtimes. Realistically sized instances of the three problem extensions can also be solved with low computational effort. For scattered storage, we note a rough tendency that runtimes increase with longer pick lists or a higher degree of duplication. In addition, we find that decoupling of picker and cart can lead to substantial cost savings depending on the speed and capacity of the picker when traveling alone, whereas additional end depots have rather limited benefits in a single-block warehouse. Summary of Contribution: Efficiently routing order pickers is of great practical interest because picking costs make up a substantial part of operational warehouse costs. For the prevalent case of a rectangular warehouse with parallel picking aisles, we present a highly effective modeling approach that covers—in addition to the standard setting—several important storage and order-picking strategies employed in modern e-commerce warehouses: scattered storage, decoupling of picker and cart, and multiple end depots. In this way, we provide practitioners as well as scientists with an easy and quick way of implementing a high-quality solution approach for routing pickers in the described settings. In addition, we shed some light on the cost benefits of the different storage and picking strategies in numerical experiments.

scholarly journals Solving methods for the quay crane scheduling problem at port of Tripoli-Lebanon.

2020 ◽  
Author(s):  
Ali Skaf ◽  
Sid Lamrous ◽  
Zakaria Hammoudan ◽  
Marie-Ange Manier
Keyword(s):  
Dynamic Programming Algorithm ◽  
Heuristic Method ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Programming Algorithm ◽  
Scheduling Problem ◽  
Exact Methods ◽  
Three Solutions ◽  
Quay Crane Scheduling ◽  
Crane Scheduling

The quay crane scheduling problem (QCSP) is a global problem and all ports around the world seek to solve it, to get an acceptable time of unloading containers from the vessels or loading containers to the vessels and therefore reducing the docking time in the terminal. This paper proposes three solutions for the QCSP in port of Tripoli-Lebanon, two exact methods which are the mixed integer linear programming and the dynamic programming algorithm, to obtain the optimal solution and one heuristic method which is the genetic algorithm, to obtain near optimal solution within an acceptable CPU time. The main objective of these methods is to minimize the unloading or the loading time of the containers and therefore reduce the waiting time of the vessels in the terminals. We tested and validated our methods for small and large random instances. Finally, we compared the results obtained with these methods for some real instances in the port of Tripoli-Lebanon.

On The Selection of Discrete Grid Systems for On-Board Micro-based Weather Routeing

1990 ◽  
Vol 43 (1) ◽  
pp. 104-117 ◽  
Author(s):  
R. H. Motte ◽  
S. Calvert
Keyword(s):  
Dynamic Programming ◽  
Dynamic Programming Algorithm ◽  
Performance Measure ◽  
Programming Algorithm ◽  
Grid Systems ◽  
Objective Performance ◽  
The Cost ◽  
Discrete Grid ◽  
Ship Speed ◽  
Selection Of

The purpose of this paper is to show the effect of incorporating various discrete grid systems in a micro-based, ship weather-routeing system, which employs Bellman's dynamic programming algorithm, and either a cost-objective or time-objective performance measure. A simple ship speed and power function is utilized, in the cost computation. The calculation of the least-cost/least-time route is briefly described, but it is the derivation of the discrete grids and their influence on the route decisions that forms the paper's emphasis. The measure of cost within this paper is necessarily notional.

scholarly journals A Survey on Advancing the DBMS Query Optimizer: Cardinality Estimation, Cost Model, and Plan Enumeration

2021 ◽  
Vol 6 (1) ◽  
pp. 86-101
Author(s):  
Hai Lan ◽  
Zhifeng Bao ◽  
Yuwei Peng
Keyword(s):  
Cost Model ◽  
Database Systems ◽  
Enumeration Algorithm ◽  
Estimation Errors ◽  
Cardinality Estimation ◽  
Execution Plan ◽  
Query Optimizer ◽  
Almost All ◽  
The Cost

AbstractQuery optimizer is at the heart of the database systems. Cost-based optimizer studied in this paper is adopted in almost all current database systems. A cost-based optimizer introduces a plan enumeration algorithm to find a (sub)plan, and then uses a cost model to obtain the cost of that plan, and selects the plan with the lowest cost. In the cost model, cardinality, the number of tuples through an operator, plays a crucial role. Due to the inaccuracy in cardinality estimation, errors in cost model, and the huge plan space, the optimizer cannot find the optimal execution plan for a complex query in a reasonable time. In this paper, we first deeply study the causes behind the limitations above. Next, we review the techniques used to improve the quality of the three key components in the cost-based optimizer, cardinality estimation, cost model, and plan enumeration. We also provide our insights on the future directions for each of the above aspects.

scholarly journals Cluster-Based Relocation of Stations for Efficient Forest Fire Management in the Province of Valencia (Spain)

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 797
Author(s):  
Miguel de Domingo ◽  
Nuria Ortigosa ◽  
Javier Sevilla ◽  
Sandra Roger
Keyword(s):  
Forest Fires ◽  
Fire Management ◽  
Historical Data ◽  
Dynamic Programming Algorithm ◽  
Programming Algorithm ◽  
Slowing Down ◽  
Forest Fire Management ◽  
Effective Manner ◽  
Fire Stations ◽  
The Cost

Forest fires are undesirable situations with tremendous impacts on wildlife and people’s lives. Reaching them quickly is essential to slowing down their expansion and putting them out in an effective manner. This work proposes an optimized distribution of fire stations in the province of Valencia (Spain) to minimize the impacts of forest fires. Using historical data about fires in the Valencia province, together with the location information about existing fire stations and municipalities, two different clustering techniques have been applied. Floyd–Warshall dynamic programming algorithm has been used to estimate the average times to reach fires among municipalities and fire stations in order to quantify the impacts of station relocation. The minimization was done approximately through k-means clustering. The outcomes with different numbers of clusters determined a predicted tradeoff between reducing the time and the cost of more stations. The results show that the proposed relocation of fire stations generally ensures faster arrival to the municipalities compared to the current disposition of fire stations. In addition, deployment costs associated with station relocation are also of paramount importance, so this factor was also taken into account in the proposed approach.

Optimization for speed regulation strategy of compound coupled hydro-mechanical transmission

2020 ◽  
pp. 095440702098056
Author(s):  
Jin Yu ◽  
Pengfei Shen ◽  
Zhao Wang ◽  
Yurun Song ◽  
Xiaohan Dong
Keyword(s):  
Fuel Consumption ◽  
Dynamic Programming Algorithm ◽  
Operating Conditions ◽  
Programming Algorithm ◽  
Speed Ratio ◽  
Mechanical Transmission ◽  
Speed Regulation ◽  
Ratio Change ◽  
Low Efficiency ◽  
Wheel Loaders

Heavy duty vehicles, especially special vehicles, including wheel loaders and sprinklers, generally work with drastic changes in load. With the usage of a conventional hydraulic mechanical transmission, they face with these problems such as low efficiency, high fuel consumption and so forth. Some scholars focus on the research to solve these issues. However, few of them take into optimal strategies the fluctuation of speed ratio change, which can also cause a lot of problems. In this study, a novel speed regulation is proposed which cannot only solve problems above but also overcome impact caused by speed ratio change. Initially, based on the former research of the Compound Coupled Hydro-mechanical Transmission (CCHMT), the basic characteristics of CCHMT are analyzed. Besides, to solve these problems, dynamic programming algorithm is utilized to formulate basic speed regulation strategy under specific operating condition. In order to reduce the problem caused by speed ratio change, a new optimization is applied. The results indicate that the proposed DP optimal speed regulation strategy has better performance on reducing fuel consumption by up to 1.16% and 6.66% in driving cycle JN1015 and in ECE R15 working condition individually, as well as smoothing the fluctuation of speed ratio by up to 12.65% and 19.01% in those two driving cycles respectively. The processes determining the speed regulation strategy can provide a new method to formulate the control strategies of CCHMT under different operating conditions particularlly under real-world conditions.

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