论文列表及评分结果
Natural discrete-event process forecasting: A decision support system.
电商所评分：1
Unconstrained multilayer switchbox routing.
电商所评分：8
Scheduling multiprocessor tasks on a dynamic configuration of dedicated processors.
电商所评分：4
A dual strategy for solving the linear programming relaxation of a driver scheduling system.
电商所评分：5
Improving the location of minisum facilities through network modification.
电商所评分：4
A center location problem with congestion.
电商所评分：3
Local convergence in a generalized Fermat-Weber problem.
电商所评分：2
Probabilisticlp distances in location models.
电商所评分：2
Location and allocation for distribution systems with transshipments and transportion economies of scale.
电商所评分：5
Locating facilities which interact: Some solvable cases.
电商所评分：8
Forecast horizons and dynamic facility location planning.
电商所评分：4
A note on the Weber location problem.
电商所评分：7
Asymptotic behavior of the Weber location problem on the plane.
电商所评分：1
Competitive location in the plane.
电商所评分：2
Hotelling's duopoly on a tree.
电商所评分：8
A multiobjective model for locating undesirable facilities.
电商所评分：3
On worst-case aggregation analysis for network location problems.
电商所评分：10
A network location-allocation model trading off flow capturing andp-median objectives.
电商所评分：10
The dual of a generalized minimax location problem.
电商所评分：1
Good solutions to discrete noxious location problems via metaheuristics.
电商所评分：5
Avoiding local optima in thep-hub location problem using tabu search and GRASP.
电商所评分：9
The capacitated standard response fire protection siting problem: Deterministic and probabilistic models.
电商所评分：3
Capacitated emergency facility siting with multiple levels of backup.
电商所评分：5
A clustering approach to the planar hub location problem.
电商所评分：6
On destination optimality in asymmetric distance Fermat-Weber problems.
电商所评分：3
Light traffic heuristic for anM/G/1 queue with limited inventory.
电商所评分：6
Demand sensitivity to space-price competition with Manhattan and Euclidean representations of distance.
电商所评分：10
Stochastic quasigradient methods for optimization of discrete event systems.
电商所评分：4
Smoothing complements and randomized score functions.
电商所评分：7
Monte Carlo (importance) sampling within a benders decomposition algorithm for stochastic linear programs.
电商所评分：4