An Optimal Operational Advisory System for a Brewery’s Energy Supply Plant

1994 ◽  
Vol 116 (1) ◽  
pp. 65-71 ◽  
Author(s):  
K. Ito ◽  
T. Shiba ◽  
R. Yokoyama ◽  
S. Sakashita
Keyword(s):  
Mixed Integer Linear Programming ◽  
Energy Supply ◽  
Numerical Solutions ◽  
Numerical Study ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Operational Cost ◽  
Hierarchical Approach ◽  
Advisory System ◽  
Integer Linear Programming Problem

An optimal operational advisory system is proposed to operate rationally a brewery’s energy supply plant from the economical viewpoint. A mixed-integer linear programming problem is formulated so as to minimize the daily operational cost subject to constraints such as equipment performance characteristics, energy supply-demand relations, and some practical operational restrictions. This problem includes lots of unknown variables and a hierarchical approach is adopted to derive numerical solutions. The optimal solution obtained by this method is indicated to the plant operators so as to support their decision making. Through the numerical study for a real brewery plant, the possibility of saving operational cost is ascertained.

scholarly journals Numerical Evaluation of Sample Gathering Solutions for Mobile Robots

2019 ◽  
Vol 9 (4) ◽  
pp. 791 ◽  
Author(s):  
Adrian Burlacu ◽  
Marius Kloetzer ◽  
Cristian Mahulea
Keyword(s):  
Mixed Integer Linear Programming ◽  
Numerical Evaluation ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Problem Instance ◽  
Storage Facility ◽  
Optimal Assignment ◽  
Integer Linear Programming Problem ◽  
Optimal Movement ◽  
The Mathematical Model

This paper applies mathematical modeling and solution numerical evaluation to the problem of collecting a set of samples scattered throughout a graph environment and transporting them to a storage facility. A team of identical robots is available, where each robot has a limited amount of energy and it can carry one sample at a time. The graph weights are related to energy and time consumed for moving between adjacent nodes, and thus, the task is transformed to a specific optimal assignment problem. The design of the mathematical model starts from a mixed-integer linear programming problem whose solution yields an optimal movement plan that minimizes the total time for gathering all samples. For reducing the computational complexity of the optimal solution, we develop two sub-optimal relaxations and then we quantitatively compare all the approaches based on extensive numerical simulations. The numerical evaluation yields a decision diagram that can help a user to choose the appropriate method for a given problem instance.

scholarly journals Implementation of a Mathematical Model to Improve Sustainability in the Handling of Transport Costs in a Distribution Network

2019 ◽  
Vol 12 (1) ◽  
pp. 63
Author(s):  
José Manuel Velarde ◽  
Susana García ◽  
Mauricio López ◽  
Alfredo Bueno-Solano
Keyword(s):  
Mathematical Model ◽  
Linear Programming ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Numerical Study ◽  
Distribution Network ◽  
Transport Cost ◽  
Mixed Integer ◽  
Distribution Area ◽  
Use Of Resources

This work considers the application of a mathematical model using mixed-integer linear programming for the vehicle routing problem. The model aims at establishing the distribution routes departing from a distribution center to each customer in order to reduce the transport cost associated with these routes. The study considers the use of a fleet of different capacities in the distribution network, which presents the special characteristic of a star network and which must meet different efficiency criteria, such as the fulfillment of each customer’s demand, the vehicle carrying capacity, work schedule, and sustainable use of resources. The intention is to find the amount of equipment suitable to satisfy the demand, thus improving the level of customer service, optimizing the use of both human and economic resources in the distribution area, and leveraging maximum vehicle capacity usage. The MILP mixed-integer linear programming mathematical model of the case study is presented, as well as the corresponding numerical study.

Robust Optimal Operation of a Gas Turbine Cogeneration Plant Under Uncertain Energy Demands

2014 ◽  
Vol 137 (2) ◽  
Author(s):  
Ryohei Yokoyama ◽  
Masashi Ohkura ◽  
Tetsuya Wakui
Keyword(s):  
Gas Turbine ◽  
Energy Supply ◽  
Numerical Study ◽  
Optimization Method ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Cogeneration Plant ◽  
Co2 Emission Reduction ◽  
Operational Strategy ◽  
Energy Demands

Some optimal operation methods based on the mixed-integer linear programming (MILP) have been proposed to operate energy supply plants properly from the viewpoints of economics, energy saving, and CO2 emission reduction. However, most of the methods are effective only under certain energy demands. In operating an energy supply plant actually, it is necessary to determine the operational strategy properly based on predicted energy demands. In this case, realized energy demands may differ from the predicted ones. Therefore, it is necessary to determine the operational strategy so that it is robust against the uncertainty in energy demands. In this paper, an optimization method based on the MILP is proposed to conduct the robust optimal operation of energy supply plants under uncertain energy demands. The uncertainty in energy demands is expressed by their intervals. The operational strategy is determined to minimize the maximum regret in the operational cost under the uncertainty. In addition, a hierarchical relationship among operation modes and on/off states of equipment, energy demands, and energy flow rates of equipment is taken into account. First, a general formulation of a robust optimal operation problem is presented, which is followed by a general solution procedure. Then, in a numerical study, the proposed method is applied to a gas turbine cogeneration plant for district energy supply. Through the study, some features of the robust optimal operation are clarified, and the validity and effectiveness of the proposed method are ascertained.

scholarly journals A new interactive approach for solving fully fuzzy mixed integer linear programming

2020 ◽  
Vol 30 (1) ◽  
pp. 71-89
Author(s):  
Goudarzi Khalili ◽  
Seyed Nasseri ◽  
Nemat Taghi-Nezhad
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Multiobjective Programming ◽  
Mixed Integer ◽  
Interactive Approach ◽  
Integer Linear Programming Problem ◽  
Novel Method ◽  
Definition Of ◽  
First Time

In this paper, a novel method to solve Fully Fuzzy Mixed Integer Linear Programming (FFMILP) problems is presented. Our method is based on the definition of membership function and a fuzzy interactive technique for solving the classical multiobjective programming. It is worthwhile to note that this is the first time that the fully fuzzy mixed integer linear programming problem is discussed and a solving method is presented. To illustrate the steps of the proposed method, some numerical examples are solved and the results are compared with other methods in the literature. Computational results present the application of the method.

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