962 resultados para Semi-infinite linear programming
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The sugarcane industry has been important in the Brazilian economy since the colonial period. The search for alternative energy sources has gained more prominence, by offering a product generating clean energy. With the opening of the Brazilian economy, the sector has undergone transformations operating in a free market environment requiring greater efficiency and competitiveness of those involved in order to stay in business. This scenario is producer/supplier independent, and social aspects related to their stay in the market. Although its share in sugarcane production is smaller than the plant itself, it is still considerable having reached around 20% to 25% in 2008 by employing labor, also production factors had an important economic impact in the regions where they operate. Therefore, this study aimed to estimate the economic efficiency and production of independent sugarcane producers in the state of Paraná through the DEA model. The Data envelopment analysis (DEA) is a nonparametric technique that, using linear programming constructs production borders from production units that employ similar technological processes to transform inputs into outputs.The results showed that of the total surveyed, 13.56% had maximum efficiency (an efficiency score equal to 1). The average efficiency under variable returns to scale (BCC-DEA) was 0.71024. One can thus conclude that for the majority of the samples collected, it might be better use of available resources to the in order to obtain the economic efficiency of the production process.
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Pós-graduação em Engenharia Elétrica - FEIS
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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This work deals with a problem of mixed integer optimization model applied to production planning of a real world factory that aims for hydraulic hose production. To optimize production planning, a mathematic model of MILP Mixed Integer Linear Programming, so that, along with the Analytic Hierarchy process method, would be possible to create a hierarchical structure of the most import criteria for production planning, thus finding through a solving software the optimum hose attribution to its respective machine. The hybrid modeling of Analytic Hierarchy Process along with Linear Programming is the focus of this work. The results show that using this method we could unite factory reality and quantitative analysis and had success on improving performance of production planning efficiency regarding product delivery and optimization of the production flow
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This paper addresses the problem of survivable lightpath provisioning in wavelength-division-multiplexing (WDM) mesh networks, taking into consideration optical-layer protection and some realistic optical signal quality constraints. The investigated networks use sparsely placed optical–electrical–optical (O/E/O) modules for regeneration and wavelength conversion. Given a fixed network topology with a number of sparsely placed O/E/O modules and a set of connection requests, a pair of link-disjoint lightpaths is established for each connection. Due to physical impairments and wavelength continuity, both the working and protection lightpaths need to be regenerated at some intermediate nodes to overcome signal quality degradation and wavelength contention. In the present paper, resource-efficient provisioning solutions are achieved with the objective of maximizing resource sharing. The authors propose a resource-sharing scheme that supports three kinds of resource-sharing scenarios, including a conventional wavelength-link sharing scenario, which shares wavelength links between protection lightpaths, and two new scenarios, which share O/E/O modules between protection lightpaths and between working and protection lightpaths. An integer linear programming (ILP)-based solution approach is used to find optimal solutions. The authors also propose a local optimization heuristic approach and a tabu search heuristic approach to solve this problem for real-world, large mesh networks. Numerical results show that our solution approaches work well under a variety of network settings and achieves a high level of resource-sharing rates (over 60% for O/E/O modules and over 30% for wavelength links), which translate into great savings in network costs.
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The emergence of wavelength-division multiplexing (WDM) technology provides the capability for increasing the bandwidth of synchronous optical network (SONET) rings by grooming low-speed traffic streams onto different high-speed wavelength channels. Since the cost of SONET add–drop multiplexers (SADM) at each node dominates the total cost of these networks, how to assign the wavelength, groom the traffic, and bypass the traffic through the intermediate nodes has received a lot of attention from researchers recently. Moreover, the traffic pattern of the optical network changes from time to time. How to develop dynamic reconfiguration algorithms for traffic grooming is an important issue. In this paper, two cases (best fit and full fit) for handling reconfigurable SONET over WDM networks are proposed. For each approach, an integer linear programming model and heuristic algorithms (TS-1 and TS-2, based on the tabu search method) are given. The results demonstrate that the TS-1 algorithm can yield better solutions but has a greater running time than the greedy algorithm for the best fit case. For the full fit case, the tabu search heuristic yields competitive results compared with an earlier simulated annealing based method and it is more stable for the dynamic case.
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Survivable traffic grooming (STG) is a promising approach to provide reliable and resource-efficient multigranularity connection services in wavelength-division-multiplexing (WDM) optical networks. In this paper, we study the STG problem in WDM mesh optical networks employing path protection at the connection level. Both dedicated-protection and shared-protection schemes are considered. Given network resources, the objective of the STG problem is to maximize network throughput. To enable survivability under various kinds of single failures, such as fiber cut and duct cut, we consider the general shared-risklink- group (SRLG) diverse routing constraints. We first resort to the integer-linear-programming (ILP) approach to obtain optimal solutions. To address its high computational complexity, we then propose three efficient heuristics, namely separated survivable grooming algorithm (SSGA), integrated survivable grooming algorithm (ISGA), and tabu-search survivable grooming algorithm (TSGA). While SSGA and ISGA correspond to an overlay network model and a peer network model, respectively, TSGA further improves the grooming results from SSGA and ISGA by incorporating the effective tabu-search (TS) method. Numerical results show that the heuristics achieve comparable solutions to the ILP approach, which uses significantly longer running times than the heuristics.
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Network survivability is one of the most important issues in the design of optical WDM networks. In this work we study the problem of survivable routing of a virtual topology on a physical topology with Shared Risk Link Groups (SRLG). The survivable virtual topology routing problem against single-link failures in the physical topology is proved to be NP-complete in [1]. We prove that survivable virtual topology routing problem against SRLG/node failures is also NP-complete. We present an improved integer linear programming (ILP) formulation (in comparison to [1]) for computing the survivable routing under SRLG/node failures. Using an ILP solver, we computed the survivable virtual topology routing against link and SRLG failures for small and medium sized networks efficiently. As even our improved ILP formulation becomes intractable for large networks, we present a congestion-based heuristic and a tabu search heuristic (which uses the congestion-based heuristic solution as the initial solution) for computing survivable routing of a virtual topology. Our experimental results show that tabu search heuristic coupled with the congestion based heuristic (used as initial solution) provides fast and near-optimal solutions.
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Survivable traffic grooming (STG) is a promising approach to provide reliable and resource-efficient multigranularity connection services in wavelength division multiplexing (WDM) optical networks. In this paper, we study the STG problem in WDM mesh optical networks employing path protection at the connection level. Both dedicated protection and shared protection schemes are considered. Given the network resources, the objective of the STG problem is to maximize network throughput. To enable survivability under various kinds of single failures such as fiber cut and duct cut, we consider the general shared risk link group (SRLG) diverse routing constraints. We first resort to the integer linear programming (ILP) approach to obtain optimal solutions. To address its high computational complexity, we then propose three efficient heuristics, namely separated survivable grooming algorithm (SSGA), integrated survivable grooming algorithm (ISGA) and tabu search survivable grooming algorithm (TSGA). While SSGA and ISGA correspond to an overlay network model and a peer network model respectively, TSGA further improves the grooming results from SSGA and ISGA by incorporating the effective tabu search method. Numerical results show that the heuristics achieve comparable solutions to the ILP approach, which uses significantly longer running times than the heuristics.
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This work deals with a problem of mixed integer optimization model applied to production planning of a real world factory that aims for hydraulic hose production. To optimize production planning, a mathematic model of MILP Mixed Integer Linear Programming, so that, along with the Analytic Hierarchy process method, would be possible to create a hierarchical structure of the most import criteria for production planning, thus finding through a solving software the optimum hose attribution to its respective machine. The hybrid modeling of Analytic Hierarchy Process along with Linear Programming is the focus of this work. The results show that using this method we could unite factory reality and quantitative analysis and had success on improving performance of production planning efficiency regarding product delivery and optimization of the production flow
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This study aimed to evaluate the relationship between the cost and energy density of diet consumed in Brazilian households. Data from the Brazilian Household Budget Survey (POF 200812009) were used to identify the main foods and their prices. Similar items were grouped, resulting in a basket of 67 products. Linear programming was applied for the composition of isoenergetic baskets, minimizing the deviation from the average household diet. Restrictions were imposed on the inclusion of items and the energy contribution of the various food groups. A reduction in average cost of diet was applied at intervals of R$0.15 to the lowest possible cost. We identified an inverse association between energy density and cost of diet (p < 0.05), and at the lowest possible cost we obtained the maximum value of energy density Restrictions on the diet's cost resulted in the selection of diets with higher energy density, indicating that cost of diet may lead to the adoption of inadequate diets in Brazil.
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Exact results on particle densities as well as correlators in two models of immobile particles, containing either a single species or else two distinct species, are derived. The models evolve following a descent dynamics through pair annihilation where each particle interacts once at most throughout its entire history. The resulting large number of stationary states leads to a non-vanishing configurational entropy. Our results are established for arbitrary initial conditions and are derived via a generating function method. The single-species model is the dual of the 1D zero-temperature kinetic Ising model with Kimball-Deker-Haake dynamics. In this way, both in finite and semi-infinite chains and also the Bethe lattice can be analysed. The relationship with the random sequential adsorption of dimers and weakly tapped granular materials is discussed.
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Electrothermomechanical MEMS are essentially microactuators that operate based on the thermoelastic effect induced by the Joule heating of the structure. They can be easily fabricated and require relatively low excitation voltages. However, the actuation time of an electrothermomechanical microdevice is higher than the actuation times related to electrostatic and piezoelectric actuation principles. Thus, in this research, we propose an optimization framework based on the topology optimization method applied to transient problems, to design electrothermomechanical microactuators for response time reduction. The objective is to maximize the integral of the output displacement of the actuator, which is a function of time. The finite element equations that govern the time response of the actuators are provided. Furthermore, the Solid Isotropic Material with Penalization model and Sequential Linear Programming are employed. Finally, a smoothing filter is implemented to control the solution. Results aiming at two distinct applications suggest the proposed approach can provide more than 50% faster actuators. (C) 2012 Elsevier B.V. All rights reserved.
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Network virtualization is a promising technique for building the Internet of the future since it enables the low cost introduction of new features into network elements. An open issue in such virtualization is how to effect an efficient mapping of virtual network elements onto those of the existing physical network, also called the substrate network. Mapping is an NP-hard problem and existing solutions ignore various real network characteristics in order to solve the problem in a reasonable time frame. This paper introduces new algorithms to solve this problem based on 0–1 integer linear programming, algorithms based on a whole new set of network parameters not taken into account by previous proposals. Approximative algorithms proposed here allow the mapping of virtual networks on large network substrates. Simulation experiments give evidence of the efficiency of the proposed algorithms.