Optimization of short-term operation of a single multipurpose reservoir — a goal programming approach

1991 ◽  
Vol 18 (3) ◽  
pp. 397-406 ◽  
Author(s):  
Karolj K. Reznicek ◽  
Slobodan P. Simonovic ◽  
C. R. Bector
Keyword(s):  
Linear Programming ◽  
Goal Programming ◽  
Reservoir Operation ◽  
Complex Model ◽  
Programming Approach ◽  
Reservoir Operations ◽  
Operations Planning ◽  
Term Operation ◽  
The Impact

The complex real-time reservoir operation model consists of flow forecasting, reservoir operations planning, and multiobjective modules. In the present paper the original reservoir operations planning module based on a linear programming (LP) formulation is substituted with a goal programming (GP) formulation. The advantage of applying goal programming instead of linear programming lies in the smaller input data requirement, and simpler model formulation. The LP approach requires two-dimensional information while the GP approach needs only one-dimensional information. The impact of change of the operations planning routine on the results of the complex model is observed and commented on a case study. The application of GP instead of LP is found viable, in certain cases even advantageous, giving a better overall objective function value. Key words: reservoir operation, optimization.

Numerical Modelling of a District Scale Groundwater Heat Pump Operation: Case Study from Colchester, UK

2021 ◽  
Author(s):  
Taha Sezer ◽  
Abubakar Kawuwa Sani ◽  
Rao Martand Singh ◽  
David P. Boon
Keyword(s):  
Large Scale ◽  
District Level ◽  
Thermal Plume ◽  
Injection Wells ◽  
Term Operation ◽  
Heating And Cooling ◽  
Groundwater Heat Pump ◽  
The Impact

<p>Groundwater heat pumps (GWHP) are an environmentally friendly and highly efficient low carbon heating technology that can benefit from low-temperature groundwater sources lying in the shallow depths to provide heating and cooling to buildings. However, the utilisation of groundwater for heating and cooling, especially in large scale (district level), can create a thermal plume around injection wells. If a plume reaches the production well this may result in a decrease in the system performance or even failure in the long-term operation. This research aims to investigate the impact of GWHP usage in district-level heating by using a numerical approach and considering a GWHP system being constructed in Colchester, UK as a case study, which will be the largest GWHP system in the UK. Transient 3D simulations have been performed pre-construction to investigate the long-term effect of injecting water at 5°C, into a chalk bedrock aquifer. Modelling suggests a thermal plume develops but does not reach the production wells after 10 years of operation. The model result can be attributed to the low hydraulic gradient, assumed lack of interconnecting fractures, and large (>500m) spacing between the production and injection wells. Model validation may be possible after a period operational monitoring.</p>

Enabling integrated business planning through big data analytics: a case study on sales and operations planning

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alexander Schlegel ◽  
Hendrik Sebastian Birkel ◽  
Evi Hartmann
Keyword(s):  
Big Data ◽  
Information Processing ◽  
Data Analytics ◽  
Single Case ◽  
Big Data Analytics ◽  
Business Planning ◽  
Operations Planning ◽  
Content Type ◽  
The Impact

PurposeThe purpose of this study is to investigate how big data analytics capabilities (BDAC) enable the implementation of integrated business planning (IBP) – the advanced form of sales and operations planning (S&OP) – by counteracting the increasing information processing requirements.Design/methodology/approachThe research model is grounded in the organizational information processing theory (OIPT). An embedded single case study on a multinational agrochemical company with multiple geographically distinguished sub-units of analysis was conducted. Data were collected in workshops, semistructured interviews as well as direct observations and enriched by secondary data from internal company sources as well as publicly available sources.FindingsThe results show the relevancy of establishing BDAC within an organization to apply IBP by providing empirical evidence of BDA solutions in S&OP. The study highlights how BDAC increase an organization's information processing capacity and consequently enable efficient and effective S&OP. Practical guidance toward the development of tangible, human and intangible BDAC in a particular sequence is given.Originality/valueThis study is the first theoretically grounded, empirical investigation of S&OP implementation journeys under consideration of the impact of BDAC.

scholarly journals A Goal Programming Approach to Nurse Scheduling with Individual Preference Satisfaction

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Pavinee Rerkjirattikal ◽  
Van-Nam Huynh ◽  
Sun Olapiriyakul ◽  
Thepchai Supnithi
Keyword(s):  
Job Satisfaction ◽  
Goal Programming ◽  
Individual Preference ◽  
Programming Approach ◽  
Nurse Scheduling ◽  
Intention To Stay ◽  
Individual Preferences ◽  
Working Shift ◽  
Shift Rotation

The use of scheduling optimization tools is essential in creating an efficient nurse shift-rotation schedule. A well-designed nurse scheduling technique can improve nurses’ job satisfaction and their intention to stay. This study develops a goal programming approach to nurse scheduling that simultaneously considers workload fairness and individual preferences on working shift and day off assignments. A case study of an operating room at a hospital in Thailand is used to illustrate the model capabilities for solving an actual nurse scheduling problem. The job satisfaction factors defined based on an interview and questionnaire survey are integrated into the model. When compared against the manual scheduling result, the optimal schedules can be implemented to improve the nurse’s perception of fairness and preference satisfaction. The analysis of fairness and multiple individual preferences based on a case study investigation is the main contribution of this study.

An Integer Programming Approach to Optimize the Plantation in Order to Reduce Global Warming

2012 ◽  
Vol 548 ◽  
pp. 767-771 ◽  
Author(s):  
C. Vanlisuta ◽  
Suksan Prombanpong
Keyword(s):  
Mathematical Model ◽  
Linear Programming ◽  
Objective Function ◽  
Programming Model ◽  
Programming Approach ◽  
Profit Function ◽  
Carbon Credit ◽  
Integer Linear Programming Model ◽  
The Mathematical Model

The objective of this paper is to determine the number and species of trees to be planted in order to maximize a profit through an integer linear programming model. The mathematical model is developed in terms of the profit function. This objective function is therefore, a difference between carbon credit revenue and costs of plantation. The economical plants are only considered in the model. Consequently, fourteen different tree species are to be investigated. The objective function is subjected to several constraints i.e. planting area, carbon sequestration and so on. The planting envelope of each tree is assigned 4 by 4 meters. In this paper, the Eastern part of Thailand is considered the case study. It is found that three kinds of plants, Copper pod, Cananga, and Bullet wood are suitable for planting. A number of trees to be planted in 1600 square meter are twenty, thirty, and fifty plants respectively. The profit earned is of 12,112 $ per year in the next fifth year.

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