This paper deals with issues regarding network planning and optimization in multi-hop wireless mesh networks (WMNs). The central focus is on mathematical programming formulations for both the uncapacitated and capacit...
详细信息
This paper deals with issues regarding network planning and optimization in multi-hop wireless mesh networks (WMNs). The central focus is on mathematical programming formulations for both the uncapacitated and capacitated joint gateway selection and routing (U/C-GSR) problem in WMNs, which are in general NP-complete, when expressed as decision problems. We detail a reformulation using the shortest path cost matrix (SPM) and prove that it gives the optimal solution when applied to the uncapacitated case. We extend the SPM formulation to the capacitated case and show computationally, by using a lower bound on the optimal solution, that it performs within a small optimality gap. Evidence from numerical investigations shows that, the proposed formulation can dramatically improve the computation time for WMNs with realistic network sizes Furthermore, a set of extensions to the basic formulation is detailed to allow modeling issues such as multi-rate transmission, restricting the number of hops in each routing sub-tree and declaring unreliable nodes as leaf nodes in the routing tree. (C) 2009 Elsevier B V All rights reserved.
An efficient integration of production and distribution plans into a unified framework is critical to achieving competitive advantage. This paper addresses the production and distribution planning problem in a supply ...
详细信息
An efficient integration of production and distribution plans into a unified framework is critical to achieving competitive advantage. This paper addresses the production and distribution planning problem in a supply chain system that involves the allocation of production volumes among the different production lines in the manufacturing plants, and the delivery of the products to the distribution centers. An integrated optimization model for production and distribution planning is proposed, with the aimed of optimally coordinating important and interrelated logistics decisions. However, a real supply chain operates in a highly dynamic and uncertain environment. Therefore, this model is transformed into fuzzy models taking into account the fuzziness in the capacity constraints, and the aspiration level of costs using different aggregation operators. The applicability and flexibility of the proposed models are illustrated through a case study in consumer goods industry. (C) 2009 Elsevier Ltd. All rights reserved.
To remain competitive, the modern industry strive for flexibility. Recently, a method for automatic generation of control code from a 3D simulation model of a flexible manufacturing system was developed. Finite automa...
详细信息
To remain competitive, the modern industry strive for flexibility. Recently, a method for automatic generation of control code from a 3D simulation model of a flexible manufacturing system was developed. Finite automata and supervisory control theory (SCT) were used to guarantee the required behaviour of the system. This paper moves one step further. A method for automatic conversion between deterministic finite automata and mixed integer linear programming (MILP) formulation is presented. This allows to efficiently combine SCT and MILP to automatically generate time-optimal, collision-free and non-blocking working schedules
The purpose of this work is to propose and test a mixed integer linear programming formulation for the problem of brain source localization. Such technique allows the localization of the minimum number of currents tha...
详细信息
The purpose of this work is to propose and test a mixed integer linear programming formulation for the problem of brain source localization. Such technique allows the localization of the minimum number of currents that are able to reconstruct evoked potentials recorded at the scalp. The algorithm makes use of binary variables in order to be less sensible to noise on input data. Some preliminary simulation results show that the algorithm is effective in source localization and robust with respect to errors on measurement data.
Identifying small groups of lines, whose removal would cause a severe blackout, is critical for the secure operation of the electric power grid. We show how power grid vulnerability analysis can be studied as a bileve...
详细信息
Identifying small groups of lines, whose removal would cause a severe blackout, is critical for the secure operation of the electric power grid. We show how power grid vulnerability analysis can be studied as a bilevel mixedinteger nonlinearprogramming problem. Our analysis reveals a special structure in the formulation that can be exploited to avoid nonlinearity and approximate the original problem as a pure combinatorial problem. The key new observation behind our analysis is the correspondence between the Jacobian matrix (a representation of the feasibility boundary of the equations that describe the flow of power in the network) and the Laplacian matrix in spectral graph theory (a representation of the graph of the power grid). The reduced combinatorial problem is known as the network inhibition problem, for which we present a mixed integer linear programming formulation. Our experiments on benchmark power grids show that the reduced combinatorial model provides an accurate approximation, to enable vulnerability analyses of real-sized problems with more than 16,520 power lines.
We address the problem of designing and planning a multi-period, multi-echelon, multi-commodity logistics network with deterministic demands. This consists of making strategic and tactical decisions: opening, closing ...
详细信息
We address the problem of designing and planning a multi-period, multi-echelon, multi-commodity logistics network with deterministic demands. This consists of making strategic and tactical decisions: opening, closing or expanding facilities, selecting suppliers and defining the product flows. We use a heuristic approach based on the linear relaxation of the original mixedintegerlinear problem (MILP). The main idea is to solve a sequence of linear relaxations of the original MILP, and to fix as many binary variables as possible at every iteration. This simple process is coupled with several rounding procedures for some key decision variables. The number of binary decision variables in the resulting MILP is small enough for it to be solved with a solver. The main benefit of this approach is that it provides feasible solutions of good quality within an affordable computation time. (C) 2010 Elsevier Ltd. All rights reserved.
This paper studies a new generalization of the regular permutation flowshop scheduling problem (PFSP) referred to as the distributed permutation flowshop scheduling problem or DPFSP. Under this generalization, we assu...
详细信息
This paper studies a new generalization of the regular permutation flowshop scheduling problem (PFSP) referred to as the distributed permutation flowshop scheduling problem or DPFSP. Under this generalization, we assume that there are a total of F identical factories or shops, each one with m machines disposed in series. A set of n available jobs have to be distributed among the F factories and then a processing sequence has to be derived for the jobs assigned to each factory. The optimization criterion is the minimization of the maximum completion time or makespan among the factories. This production setting is necessary in today's decentralized and globalized economy where several production centers might be available for a firm. We characterize the DPFSP and propose six different alternative mixed integer linear programming (MILD) models that are carefully and statistically analyzed for performance. We also propose two simple factory assignment rules together with 14 heuristics based on dispatching rules, effective constructive heuristics and variable neighborhood descent methods. A comprehensive computational and statistical analysis is conducted in order to analyze the performance of the proposed methods: (C) 2009 Elsevier Ltd. All rights reserved.
The design of computer experiments is an important step in black-box evaluation and optimization processes. When dealing with multiple black-box functions the need often arises to construct designs for all black boxes...
详细信息
The design of computer experiments is an important step in black-box evaluation and optimization processes. When dealing with multiple black-box functions the need often arises to construct designs for all black boxes jointly, instead of individually. These so-called nested designs are particularly useful as training and test sets for fitting and validating metamodels, respectively. Furthermore, nested designs can be used to deal with linking parameters and sequential evaluations. In this paper, we introduce one-dimensional nested maximin designs. We show how to nest two designs optimally and develop a heuristic to nest three and four designs. These nested maximin designs can be downloaded from the website http://***. Furthermore, it is proven that the loss in space-fillingness, with respect to traditional maximin designs, is at most 14.64 and 19.21%, when nesting two and three designs, respectively.
We consider three easy-to-implement methods for the piecewise linear approximation of functions of two variables. We experimentally evaluate their approximation quality, and give a detailed description of how the meth...
详细信息
We consider three easy-to-implement methods for the piecewise linear approximation of functions of two variables. We experimentally evaluate their approximation quality, and give a detailed description of how the methods can be embedded in a MILP model. The advantages and drawbacks of the three methods are discussed on numerical examples. (C) 2009 Elsevier B.V. All rights reserved.
This paper describes a novel procedure to generate continuously differentiable optimal flight trajectories in the presence of arbitrarily shaped no-fly zones and obstacles having a fixed position in time. The operatio...
详细信息
This paper describes a novel procedure to generate continuously differentiable optimal flight trajectories in the presence of arbitrarily shaped no-fly zones and obstacles having a fixed position in time. The operational flight scenario is first discretized with 9 finite dimensional grid of positions-directions pairs. A weighted and oriented graph is then defined for which the nodes are the earlier mentioned grid points and for which the arcs correspond to minimum length trajectories compliant with obstacle avoidance constraints. Arcs are obtained via solving convex quadratic programming optimization problems that can also account for geometrical constraints such as trajectory curvature limitations. The problem of finding an optimal trajectory be tween two nodes of the so-called core paths graph is then solved via a minimum cost path search algorithm. In a real-time application perspective, the generation of the core paths graph is computationally cumbersome. Moreover, the aircraft position and direction rarely coincide with one of the graph nodes. However, if the graph is built offline and stored, the definition of an optimal trajectory connecting any points of the space domain requires a reduced computational effort. The particular case of piecewise polynomial trajectories minimizing a flight path's length, compliant with constraints on curvature and flight-path angles, is fully developed. Two- and three-dimensional examples are discussed to show the applicability as well as the effectiveness of the technique.
暂无评论