Construction Enterprises Bidding Decision-Making Based on Linear Programming

2009 ◽  
Author(s):  
Liu Jian-Bing
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Construction Enterprises

scholarly journals Farm-Boarding School Management: Linear Programming Contributions in the Search of Self-Sufficiency and Optimization

2017 ◽  
Vol 9 (3) ◽  
pp. 59
Author(s):  
Carina Simionato de Barros ◽  
Gabriela Geraldi Mendonça ◽  
Augusto Hauber Gameiro
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Programming Model ◽  
Safety Margin ◽  
Boarding School ◽  
Point Of View ◽  
Technical Programs ◽  
Modeling Process ◽  
Self Sufficiency ◽  
Education Of Students

Farm schools offer a learning environment for the education of students in Agricultural Technical Programs and offer this program adopting boarding systems (“farm-boarding schools” or “FBS”). The big challenge in FBS is balancing education and production, that is, provide resources for practical classes and at the same time provide food for farm residents from a pre-defined budget by the sponsoring institution. The aim of this paper is to present a linear programming model to plan and optimize FBS production and supply. The model was applied in two FBS in Brazil. The model developed could show the complexity of the FBS system, which features a variety of productions and the interactions among them. The modeling process presented positive results from a technical and managerial point of view, including people management. The formulated model showed an optimized scenario which extended the managers’ analysis horizon and allowed safer decision making. The system’s complexity hampers dialogue between the farm-boarding school team and managers. From the modeling process and the standardization of data and generated results, there was a greater safety margin to present investment proposals and analyzes, accelerating the decision-making process, which was a positive addition to the system.

scholarly journals Measuring the technical efficiency of local banks in UAE using rough bi-level linear programming technique

2015 ◽  
Vol 1 (1) ◽  
pp. 26
Author(s):  
Doaa Wafik ◽  
O. E. Emam
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Technical Efficiency ◽  
Auxiliary Problem ◽  
Optimal Solution ◽  
Objective Functions ◽  
Programming Technique ◽  
Decision Making Problem ◽  
Linear Objective Functions ◽  
Linear Programming Technique

The aim of this paper is to use a bi-level linear programming technique with rough parameters in the constraints, for measuring the technical efficiency of local banks in UAE and Egypt, while the proposed linear objective functions will be maximized for different goals. Based on Dauer's and Krueger's goal programmingmethod, the described approach was developed to deal with the bi-level decision-making problem. The concept of tolerance membership function together was used to generate the optimal solution for the problem under investigation. Also an auxiliary problem is discussed to illustrate the functionality of the proposed approach.

Goal Programming and Its Variants

2011 ◽  
pp. 410-417
Author(s):  
John Wang ◽  
Dajin Wang ◽  
Aihua Li
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Goal Programming ◽  
Multicriteria Decision Making ◽  
Industrial Applications ◽  
Multiple Objective ◽  
Multi Criteria Decision Making ◽  
Powerful Method ◽  
Noticeable Increase ◽  
New Type

Within the realm of multicriteria decision making (MCDM) exists a powerful method for solving problems with multiple objectives. Goal programming (GP) was the first multiple-objective technique presented in the literature (Dowlatshahi, 2001). The premise of GP traces its origin back to a linear programming study on executive compensation in 1955 by Charnes, Cooper, and Ferguson even though the specific name did not appear in publications until the 1961 textbook entitled Management Models and Industrial Applications of Linear Programming, also by Charnes and Cooper (Schniederjans, 1995). Initial applications of this new type of modeling technique demonstrated its potential for a variety of applications in numerous different areas. Until the middle of the 1970s, GP applications reported in the literature were few and far between. Since that time, primarily due to influential works by Lee and Ignizio, a noticeable increase of published GP applications and technical improvements has been recognized. The number of case studies, along with the range of fields, to which GP has been and still is being applied is impressive, as shown in surveys by Romero (1991) and Aouni and Kettani (2001). It can be said that GP has been, and still is, the “most widely used multi-criteria decision making technique” (Tamiz, Jones, & Romero, 1998, p. 570).

scholarly journals Robust Linear Programming and Its Application to Water and Environmental Decision-Making under Uncertainty

2018 ◽  
Vol 11 (1) ◽  
pp. 33 ◽  
Author(s):  
Yang Zhou ◽  
Bo Yang ◽  
Jingcheng Han ◽  
Yuefei Huang
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Robust Optimization ◽  
Water Quality Management ◽  
Optimization Techniques ◽  
Programming Approach ◽  
Decision Making Under Uncertainty ◽  
Environmental Decision Making ◽  
Robust Linear Programming ◽  
Environmental Decision

In this study, we introduce a robust linear programming approach for water and environmental decision-making under uncertainty. This approach is of significant practical utility to decision makers for obtaining reliable and robust management decisions that are “immune” to the uncertainty attributable to data perturbations. The immunization guarantees that the chosen robust management plan will be implementable with no violation of the mandatory constraints of the problem being studied—i.e., natural resource supply constraint, environmental carrying capacity constraint, environmental pollution control constraint, etc.—and that the actual value of the objective will be no worse than the given estimation if the perturbations of data fall within the specified uncertainty set. A simplified example in regional water quality management is provided to help water and environmental practitioners to better understand how to implement robust linear programming from the perspective of application, as well as to illustrate the significance and necessity of implementing robust optimization techniques in real-world practices. Robust optimization is a growing research field that requires more interdisciplinary research efforts and engagements from water and environmental practitioners. Both may benefit from the advances of management science.

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