This study presents an evaluation of heuristics that reconfigure a multi-layer network logical topology for efficiently accommodating variable traffic patterns. Numerical results show that reconfiguration is useful if...
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This study presents an evaluation of heuristics that reconfigure a multi-layer network logical topology for efficiently accommodating variable traffic patterns. Numerical results show that reconfiguration is useful if the network is not heavily loaded.
In this paper, we consider a special discount where: (1) the price breaks depend on the size of the order quantities, (2) independent products¿ sales volume affect the prices and discounts of the other products a...
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ISBN:
(纸本)9781424426294
In this paper, we consider a special discount where: (1) the price breaks depend on the size of the order quantities, (2) independent products¿ sales volume affect the prices and discounts of the other products and (3) all products must be sold as a bundle. In this circumstance, which the buyer wants to buy multi-product and suppliers also offer the special discount, the problem becomes more complicated. To formulate the problem, multi-objective mixed integer linear programming (MOMILP) is used to define the optimum quantities among the selected suppliers. The problem includes the three objective functions: to minimize the inverse Total Value of Purchasing (TVP), the total cost and total defect rate, while satisfying capacity and demand requirement constraints. In order to solve the model, a single objective function is used that considers relative importance of the goals. A numerical example is given to illustrate how the multi-objective model is applied.
We consider a version of the total flow time single machine scheduling problem where uncertainty about processing times is taken into account. Namely an interval of equally possible processing times is considered for ...
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This paper presents a profit-based model for short-term hydro scheduling adapted to pool-based electricity markets. The objective is to determine a feasible and realistic operation of a set of coupled hydro units belo...
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This paper presents a profit-based model for short-term hydro scheduling adapted to pool-based electricity markets. The objective is to determine a feasible and realistic operation of a set of coupled hydro units belonging to a small or medium-size hydroelectric company in order to build the generation bids for the next 24 hourly periods. The company is assumed to be price-taker, and therefore, market prices are considered exogenous variables and modeled via scenarios generated by an Input/Output Hidden Markov Model (IOHMM). In order to be protected against low prices scenarios, two different risk-aversion criteria are introduced in the model: a minimum profit constraint and a minimum conditional Value-at-Risk (CVaR) requirement, which can be formulated linearly in the context of the optimization problem. In order to ensure a feasible operation, the model takes into account a very detailed representation of the generating units, which includes forbidden discharge intervals, spatial-temporal constraints among cascaded reservoirs, etc. The non-linear relationship among the electrical power, the net-head and the turbine water discharge is treated by means of an under-relaxed iterative procedure where net-heads are successively update until convergence is reached. During each algorithm stage, previous iterations' information is used to build the input-output curves. This way, the hydro scheduling problem can be formulated as a MILP optimization problem, where unit-commitment decisions are modeled by means of binary variables. The model has been successfully applied to a real-size example case, which is also presented in this paper. (C) 2006 Elsevier B.V. All rights reserved.
The selection of the branching variable can greatly affect the speed of the branch and bound solution of a mixed-integer or integerlinear program. Traditional approaches to branching variable selection rely on estima...
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The selection of the branching variable can greatly affect the speed of the branch and bound solution of a mixed-integer or integerlinear program. Traditional approaches to branching variable selection rely on estimating the effect of the candidate variables on the objective function. We present a new approach that relies on estimating the impact of the candidate variables on the active constraints in the current LP relaxation. We apply this method to the problem of finding the first feasible solution as quickly as possible. Empirical experiments demonstrate a significant improvement compared to a state-of-the art commercial MIP solver.
A study on multivehicle trajectory planning for cooperative reconnaissance problems is presented. Specifically, this work develops understanding and insights into how vehicles cooperate in reconnaissance type missions...
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A study on multivehicle trajectory planning for cooperative reconnaissance problems is presented. Specifically, this work develops understanding and insights into how vehicles cooperate in reconnaissance type missions in which target information is maximized. The performance metric used to guide the cooperation study is the amount of information, defined using the Fisher information matrix, that the sensing vehicles gather over their planned trajectory. A receding horizon optimal control formulation is developed and solved for trajectories that yield maximum information. High-risk zones and vehicle/terminal constraints are also are considered. Trends include the following: 1) vehicles with nonsymmetric sensors tend to triangulate as they get close to the target;2) vehicles tend to move toward stationary targets as quickly as possible;3) the addition of a third vehicle exhibits at least 50% less performance improvement than the addition of the second vehicle, and even less for nonsymmetric sensors.;4) optimization for multiple vehicles and targets is a strong function of target to target distances and sensor uncertainty symmetry;and 5) short planning horizons are preferable for moving targets.
In this paper we consider the capacitated multi-facility Weber problem with the Euclidean, squared Euclidean, and l(p)- distances. This problem is concerned. with locating in capacitated facilities in the Euclidean pl...
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In this paper we consider the capacitated multi-facility Weber problem with the Euclidean, squared Euclidean, and l(p)- distances. This problem is concerned. with locating in capacitated facilities in the Euclidean plane to satisfy the demand of n customers with the minimum total transportation cost. The demand and location of each customer are known a priori and the transportation cost between customers and facilities is proportional to the distance between them. We first present a mixed integer linear programming approximation of the problem. We then propose new heuristic solution methods based on this approximation. computational results on benchmark instances indicate that the new methods are both accurate and efficient.
In this paper we study a 1.5-dimensional cutting stock and assortment problem which includes determination of the number of different widths of roll stocks to be maintained as inventory and determination of how these ...
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In this paper we study a 1.5-dimensional cutting stock and assortment problem which includes determination of the number of different widths of roll stocks to be maintained as inventory and determination of how these roll stocks should be cut by choosing the optimal cutting pattern combinations. We propose a new multi-objective mixed integer linear programming (MILP) model in the form of simultaneously minimization two contradicting objectives related to the trim loss cost and the combined inventory cost in order to fulfill a given set of cutting orders. An equivalent nonlinear version and a particular case related to the situation when a producer is interested in choosing only a few number of types among all possible roll sizes, have also been considered. A new method called the conic scalarization is proposed for scalarizing non-convex multi-objective problems and several experimental tests are reported in order to demonstrate the validity of the developed modeling and solving approaches. (c) 2006 Elsevier B.V. All rights reserved.
As operational costs and equipment depreciation in the TFT-LCD (thin film transistor-liquid crystal display) industry are a high percentage of the total cost, most manufacturers usually fully utilise their production ...
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As operational costs and equipment depreciation in the TFT-LCD (thin film transistor-liquid crystal display) industry are a high percentage of the total cost, most manufacturers usually fully utilise their production capacity to reduce the average unit cost. However, when the market demand is less than the supply the stock of panels increases;this forces manufacturers to instigate a price war to reduce levels of stock and results in a wide fluctuation in panel prices. Inventory stocks of panels could be decreased by optimising the product mix. This will help manufacturers to reduce the risk of holding stocks, increase profit, and improve competitive advantage. This study uses mixed integer linear programming (MILP) to construct a product mix for the TFT-LCD industry given the conditions of profit, productivity, raw materials supply, and market demand. A case study shows that this model is proven to be effective in generating product mix for the TFT-LCD industry while improving profit. The product mix generated by this model can provide a reference for the sales department for orders and shipping, for the production department for the order quantity, and for master production scheduling for each product.
The paper studies the capacity planning problem in the TFT-LCD production chain. Due to two significant trends, the capacity planning decision gradually becomes an important strategic issue to which TFT-LCD industry p...
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ISBN:
(纸本)9781424411177
The paper studies the capacity planning problem in the TFT-LCD production chain. Due to two significant trends, the capacity planning decision gradually becomes an important strategic issue to which TFT-LCD industry paid attention. First is the increase of product types which causes a wide range of product groups, such as mobile, monitor, notebook, TV and industrial display are produced. The second trend is the advances of new technology which cause multiple generations of technologies coexist in each manufacturing stage and production site. This paper proposes a mixed integer linear programming (MILP) to formulate the capacity planning which considers many practical characteristics and constraints in TFT-LCD production chain. A heuristic algorithm is developed to solve the MILP model.
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