1,720,994 research outputs found
Data from: Using branch-and-bound algorithms to optimize selection of a fixed-size breeding population under a relatedness constraint
No full textTree breeders often face the challenge of conserving genetic diversity, while at the same time maximizing response to selection. When selecting advanced-generation breeding populations, the best-performing candidates will quite often be closely related and selecting them without consideration of their relatedness will very quickly erode genetic diversity. Optimal selection will not completely avoid kinship, but rather maximize gain while imposing a constraint on average relatedness. Genetic contributions are most easily optimized if breeders can manage a real, continuous distribution of contributions from parents. While generally possible when establishing seed orchards, unequal contributions to a breeding population may present difficult and time-consuming operational constraints. In these situations, a specified number of parents contributing equally may be a preferred configuration for the breeding population. Here we formulate the selection of a fixed-size breeding population while imposing a constraint on relatedness of the population members. The problem is expressed as a Mixed Integer Quadratically Constrained Optimization (MIQCO) and solved using branch-and-bound techniques (BB). An open-source solver, dsOpt, was developed and embedded into a user-friendly tool, OPSEL, designed to simplify the process of optimizing selection of breeding populations. Case studies optimizing selection of breeding populations for Scots pine and loblolly pine illustrate the superiority of the BB solution compared with selection from ranked lists with restrictions on numbers of genotypes contributed by each full-sib family, and with solutions from GENCONT, a publically available optimum selection program using an algorithm with Lagrangian multipliers. The case studies also illustrate the extreme differences that can occur with respect to time required to confirm the optimality of solutions found by BB
Efficient storage of pareto points in biobjective mixed integer programming
Full text linkIn biobjective mixed integer linear programs (BOMILPs), two linear objectives are minimized over a polyhedron while restricting some of the variables to be integer. Since many of the techniques for finding or approximating the Pareto set of a BOMILP use and update a subset of nondominated solutions, it is highly desirable to efficiently store this subset. We present a new data structure, a variant of a binary tree that takes as input points and line segments in 2 and stores the nondominated subset of this input. When used within an exact solution procedure, such as branch and bound (BB), at termination this structure contains the set of Pareto optimal solutions. We compare the efficiency of our structure in storing solutions to that of a dynamic list, which updates via pairwise comparison. Then we use our data structure in two biobjective BB techniques available in the literature and solve three classes of instances of BOMILP, one of which is generated by us. The first experiment shows that our data structure handles up to 107 points or segments much more efficiently than a dynamic list. The second experiment shows that our data structure handles points and segments much more efficiently than a list when used in a BB
Multi-layer MPLS network design: The impact of statistical multiplexing
No full textThe possibility of adding multi protocol label switching (MPLS) support to transport networks is considered an impor- tant opportunity by telecom carriers that want to add packet services and applications to their networks. However, the question arises whether it is suitable to have MPLS nodes just at the edge of the network to collect packet traffic from users, or to introduce also MPLS facilities on a subset of the core nodes in order to exploit packet switching flexibility and multiplexing, thus inducing a better bandwidth allocation. In this paper, we propose a mathematical programming model for the design of two-layer networks where MPLS is considered on top of transport networks (SDH or WDM depending on required link speed). Our models take into account the tradeoff between the cost of adding MPLS support in the core nodes and the savings in the link bandwidth allocation due to the statistical multiplexing and the traffic groom- ing effects induced by MPLS nodes. The traffic matrix specifies for each point-to-point request a pair of values: a mean traffic value and an additional one. Using this traffic model, the effect of statistical multiplexing on a link allows to allocate a capacity equal to the sum of all the mean values of the traffic demands routed on the link and only the highest additional one. We propose a path-based Mixed Integer Programming (MIP) model for the problem of optimizing the number and location of MPLS nodes in the network and the link capacities. We apply Lagrangian relaxation to this model and use the subgradient method to obtain a lower bound of the network cost. As the number of path variables used to model the rout- ing grows exponentially with the graph size, we use an initially limited number of variables and a column generation approach. We also introduce a heuristic approach to get a good feasible solution. Computational results are reported for small size and real-world instances
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
A primal algorithm for the weighted minimum covering ball problem in Rn
No full textThe nonlinear programming problem of finding the minimum covering ball of a finite set of points in Rn, with a positive weight corresponding to each point, is solved by a directional search method. At each iteration, the search path is either a ray or the arc of a circle and is determined by bisectors of points. Each step size along the search path is determined explicitly. The primal algorithm is shown to search along the farthest point Voronoi diagram of the given points. We provide computational results that show the efficiency of the algorithm when compared to general convex nonlinear optimization solvers
- …
