Search results for "Linear programming"
showing 10 items of 137 documents
EABOT – Energetic analysis as a basis for robust optimization of trigeneration systems by linear programming
2008
Abstract The optimization of synthesis, design and operation in trigeneration systems for building applications is a quite complex task, due to the high number of decision variables, the presence of irregular heat, cooling and electric load profiles and the variable electricity price. Consequently, computer-aided techniques are usually adopted to achieve the optimal solution, based either on iterative techniques, linear or non-linear programming or evolutionary search. Large efforts have been made in improving algorithm efficiency, which have resulted in an increasingly rapid convergence to the optimal solution and in reduced calculation time; robust algorithm have also been formulated, ass…
An Effective Multirestart Deterministic Annealing Metaheuristic for the Fleet Size and Mix Vehicle-Routing Problem with Time Windows
2008
This paper presents a new deterministic annealing metaheuristic for the fleet size and mix vehicle-routing problem with time windows. The objective is to service, at minimal total cost, a set of customers within their time windows by a heterogeneous capacitated vehicle fleet. First, we motivate and define the problem. We then give a mathematical formulation of the most studied variant in the literature in the form of a mixed-integer linear program. We also suggest an industrially relevant, alternative definition that leads to a linear mixed-integer formulation. The suggested metaheuristic solution method solves both problem variants and comprises three phases. In Phase 1, high-quality init…
Fuzzy predictive controller design using ant colony optimization algorithm
2014
In this paper, an approach for designing an adaptive fuzzy model predictive control (AFMPC) based on the Ant Colony Optimization (ACO) is studied. On-line adaptive fuzzy identification is used to identify the system parameters. These parameters are used to calculate the objective function based on predictive approach and structure of RST control. The optimization problem is solved based on an ACO algorithm, used at the optimization process in AFMPC to calculate a sequence of future RST control actions. The obtained simulation results show that proposed approach provides better results compared with Proportional Integral-Ant Colony Optimization (PI-ACO) controller and adaptive fuzzy model pr…
Two-Player Noncooperative Games over a Freight Transportation Network''
2004
A game between two players acting on the same road transportation network is considered in this paper. The first player aims at minimizing the transportation costs, whereas the second player aims at maximizing her profit (or, in general, her utility) that is proportional to the flow passing through the arcs under her control. We introduce bilevel linear programming formulations for this problem. We derive conditions of existence and properties of the equilibrium points and propose an algorithm finding a local optimal solution. Finally, we present an application of the model to a real system involving trucks travelling through Europe from a Middle Eastern country.
An LP-based hyperparameter optimization model for language modeling
2018
In order to find hyperparameters for a machine learning model, algorithms such as grid search or random search are used over the space of possible values of the models hyperparameters. These search algorithms opt the solution that minimizes a specific cost function. In language models, perplexity is one of the most popular cost functions. In this study, we propose a fractional nonlinear programming model that finds the optimal perplexity value. The special structure of the model allows us to approximate it by a linear programming model that can be solved using the well-known simplex algorithm. To the best of our knowledge, this is the first attempt to use optimization techniques to find per…
Financing of Productive Investments: A Model with Coordinated Scenarios
2015
This research raises a company that knows the cash requirements to purchase capital equipments in order to satisfy the demand for the products of each of the proposed scenarios. The company is negotiating with credit institutions a series of loans at different interest rates. Also, the company can make capital increases. A model focused on the financial needs using scenarios allows us to combine funding sources to cover the costs of the acquisition of production equipment to meet the demand for each scenario. This combination remunerates own financing, settles interest and repays the borrowed capital. The results indicate that the model is robust and minimizes the financial cost of a possib…
Bootstrapping profit change: An application to Spanish banks
2012
The aim of this study is to provide a tool which enables us to conduct statistical analysis in the context of changes in productivity and profit. We build on previous initiatives to decompose profit change into mutually exclusive and exhaustive sources. To do this we use distance functions, which are calculated empirically using linear programming techniques. However, we may not learn a great deal by solving these linear programs unless methods of statistical analysis are used to examine the properties of the relevant estimators. Our purpose is to provide a methodology based on bootstrap that allows us to conduct statistical inference for the profit change decomposition. Thus, it will be po…
An Approach to the Automatic Comparison of Reference Point-Based Interactive Methods for Multiobjective Optimization
2021
Solving multiobjective optimization problems means finding the best balance among multiple conflicting objectives. This needs preference information from a decision maker who is a domain expert. In interactive methods, the decision maker takes part in an iterative process to learn about the interdependencies and can adjust the preferences. We address the need to compare different interactive multiobjective optimization methods, which is essential when selecting the most suited method for solving a particular problem. We concentrate on a class of interactive methods where a decision maker expresses preference information as reference points, i.e., desirable objective function values. Compari…
Improving the Representativeness of a Simple Random Sample: An Optimization Model and Its Application to the Continuous Sample of Working Lives
2020
This paper proposes an optimization model for selecting a larger subsample that improves the representativeness of a simple random sample previously obtained from a population larger than the population of interest. The problem formulation involves convex mixed-integer nonlinear programming (convex MINLP) and is, therefore, NP-hard. However, the solution is found by maximizing the size of the subsample taken from a stratified random sample with proportional allocation and restricting it to a p-value large enough to achieve a good fit to the population of interest using Pearson&rsquo
Capacity and Energy-Consumption Optimization for the Cluster-Tree Topology in IEEE 802.15.4
2011
International audience; 802.15.4 proposes to use a cluster-tree hierar- chy to organize the transmissions in Wireless Sensor Networks. In this letter, we propose a framework to analyze formally the capacity and the energy consumption of this structure. We derive a Mixed Integer Linear Programming (MILP) formulation to obtain a topology compliant with the standard. This formulation provides the optimal solution for the network capacity: this con- stitutes an upper bound for any distributed algorithms permitting to construct a cluster-tree. This framework can also be used to evaluate the capacity and to compare quantitatively different cluster-tree algorithms.