Foulke Consumer Products, Inc.: The Southeast Region

2017 ◽  
pp. 1-8
Author(s):  
Robert L. Carraway ◽  
William Hosler
Keyword(s):  
Linear Programming ◽  
Facility Location ◽  
Consumer Products ◽  
Location Model ◽  
Distribution Problem ◽  
Southeast Region ◽  
The Core ◽  
Lp Model

At the core of this case is a distribution, or sourcing, problem that can be modeled and solved using linear programming (LP). There are also issues of whether to build (a) new plant(s)––and if so, what the capacity should be––and whether to expand or close one or more of the existing plants. These latter issues can be analyzed using a 0/1 LP facility-location model. Alternatively, because the number of options is limited, they can be analyzed using the straight LP model of the distribution problem as a tool to facilitate analysis.

Multifunzionalitŕ e sviluppo rurale in Africa: un'analisi a livello household

2009 ◽  
pp. 31-63
Author(s):  
Filippo Arfini ◽  
Fabio Landini
Keyword(s):  
Linear Programming ◽  
Rural Development ◽  
Quantitative Evaluation ◽  
Technological Progress ◽  
Policy Design ◽  
Rural Households ◽  
Livelihood Strategies ◽  
Economic Sustainability ◽  
Lp Model

- This work offers an interpretation of the role that multifunctionality plays in the policies that sustain rural development. Assuming as a reference the livelihood approach, we analyse multifunctionality within a framework which differs from the usual Wto negotiations. We reappraise its significance as a variable that reinforces the livelihood strategies of the rural households. In terms of policy design we analyse the costs of the secondary services and the variables that allow for their reduction. A quantitative evaluation is then carried out on the basis of an LP model taking a multifunctional farm in Africa. The results obtained are that: multifunctionality is very costly; most of the private costs of multifunctionality are due to constraints on specialisation in production; both coupled and de-coupled payment sustain multifunctionality but in different ways; technological progress is a key variable for economic sustainability.EconLit Classification: C020, Q010, Q120, Q180Keywords: Multifunctionality, Rural Development, Livelihood Approach, Linear Programming

scholarly journals From Linear Programming Model to Mixed Integer Linear Programming Model for the Simultaneous Optimisation of Water Allocation and Reservoir Location in River Systems

Proceedings ◽  
2018 ◽  
Vol 2 (11) ◽  
pp. 594 ◽  
Author(s):  
Jaime Veintimilla-Reyes ◽  
Annelies De Meyer ◽  
Dirk Cattrysse ◽  
Jos Van Orshoven
Keyword(s):  
Linear Programming ◽  
Network Flow ◽  
Water Allocation ◽  
Programming Model ◽  
Water Levels ◽  
Linear Programming Model ◽  
Mixed Integer ◽  
Network Configuration ◽  
Spatially Distributed ◽  
Lp Model

The allocation of water flowing through a river-with-reservoirs system to optimally meet spatially distributed and temporally variable demands can be conceived as a Network Flow Optimisation (NFO) problem and addressed by Linear Programming (LP). In this paper we present an extension of the strategic NFO-LP model to simultaneously optimise the allocation of water and the location of one or more reservoirs. The applicability of the MILP model has been illustrated by applying it to a hypothetical river network configuration consisting of seven candidate reservoir nodes and seven demand nodes, and by comparing the outcome (water levels in selected reservoir, penalties) with the values obtained by the original LP-model for the same network with six reservoirs present.

scholarly journals A Facility Location Model for Air Pollution Detection

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
G. Lancia ◽  
F. Rinaldi ◽  
P. Serafini
Keyword(s):  
Genetic Algorithm ◽  
Air Pollution ◽  
Air Quality ◽  
Mathematical Models ◽  
Facility Location ◽  
Large City ◽  
Location Model ◽  
Practical Algorithms ◽  
Pollution Detection ◽  
The City

We describe mathematical models and practical algorithms for a problem concerned with monitoring the air pollution in a large city. We have worked on this problem within a project for assessing the air quality in the city of Rome by placing a certain number of sensors on some of the city buses. We cast the problem as a facility location model. By reducing the large number of data variables and constraints, we were able to solve to optimality the resulting MILP model within minutes. Furthermore, we designed a genetic algorithm whose solutions were on average very close to the optimal ones. In our computational experiments we studied the placement of sensors on 187 candidate bus routes. We considered the coverage provided by 10 up to 60 sensors.

Research on Mixed Intelligent Arithmetic of Reuse Reverse Logistics Centers' Location Model

2014 ◽  
Vol 945-949 ◽  
pp. 3246-3251 ◽  
Author(s):  
Lu Feng Dai ◽  
Xi Fu Wang
Keyword(s):  
Genetic Algorithm ◽  
Linear Programming ◽  
Stochastic Simulation ◽  
Reverse Logistics ◽  
Random Variables ◽  
Location Model ◽  
Logistics Center ◽  
Center Location

The paper builds the model of direct reuse reverse logistics center location followed by the uncertainty random variables of the demand of retailers and the recovery of collection points. This model assumes that the enterprises are expanding on the traditional network. For the random variables, they will be solved by using stochastic simulation, genetic algorithm and linear programming, and numericai exampie is presented.

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