Search results for "discrete optimization"
showing 8 items of 8 documents
A decomposition approach for multidimensional knapsacks with family-split penalties
2022
The optimization of Multidimensional Knapsacks with Family-Split Penalties has been introduced in the literature as a variant of the more classical Multidimensional Knapsack and Multi-Knapsack problems. This problem deals with a set of items partitioned in families, and when a single item is picked to maximize the utility, then all items in its family must be picked. Items from the same family can be assigned to different knapsacks, and in this situation split penalties are paid. This problem arises in real applications in various fields. This paper proposes a new exact and fast algorithm based on a specific Combinatorial Benders Cuts scheme. An extensive experimental campaign computational…
Algorithms for Rational Discrete Least Squares Approximation Part I: Unconstrained Optimization
1976
In this paper a modification of L. Wittmeyer’s method ([1], [14]) for rational discrete least squares approximation is given which corrects for its failure to converge to a non-optimal point in general. The modification makes necessary very little additional computing effort only. It is analysed thoroughly with respect to its conditions for convergence and its numerical properties. A suitable implementation is shown to be benign in the sense of F. L. Bauer [2]. The algorithm has proven successful even in adverse situations.
A Hybrid Strategic Oscillation with Path Relinking Algorithm for the Multiobjective k-Balanced Center Location Problem
2021
This paper presents a hybridization of Strategic Oscillation with Path Relinking to provide a set of high-quality nondominated solutions for the Multiobjective k-Balanced Center Location problem. The considered location problem seeks to locate k out of m facilities in order to serve n demand points, minimizing the maximum distance between any demand point and its closest facility while balancing the workload among the facilities. An extensive computational experimentation is carried out to compare the performance of our proposal, including the best method found in the state-of-the-art as well as traditional multiobjective evolutionary algorithms.
A Binary Particle Swarm Optimization Algorithm for a Double Auction Market
2007
In this paper, we shall show the design of a multi-unit double auction (MDA) market. It should be enough robust, flexible and sufficiently efficient in facilitating exchanges. In a MDA market, sellers and buyers submit respectively asks and bids. A trade is made if a buyers bid exceeds a sellers ask. A sellers ask may match several buyers bids and a buyers bid may satisfy several sellers asks. The trading rule of a market defines the organization, information exchange process, trading procedure and clearance rules of the market. The mechanism is announced before the opening of the market so that every agent knows how the market will operate in advance. These autonomous agents pursue their o…
Multi-objective discrete optimization of laminated structures
2002
Abstract The paper is dedicated to the multi-objective optimal design of laminated composite structures. In order to provide sound-engineering designs, a few alternative and/or conflicting objectives must be taken into account. It is reasonable to consider the multi-objective optimization as a sensible enrichment with respect to single objective optimization, since the solutions are enforced to result optimal at the same time with respect to different objectives. Multi-objective optimization methods gained in the last years a growing interest in engineering, due to the possibility to determine a design possessing at the same time optimality with respect to different conflicting requirements…
Asymmetry matters: Dynamic half-way points in bidirectional labeling for solving shortest path problems with resource constraints faster
2017
Abstract With their paper “Symmetry helps: Bounded bi-directional dynamic programming for the elementary shortest path problem with resource constraints” [Discrete Optimization 3, 2006, pp. 255–273] Righini and Salani introduced bounded bidirectional dynamic programming (DP) as an acceleration technique for solving variants of the shortest path problem with resource constraints (SPPRC). SPPRCs must be solved iteratively when vehicle routing and scheduling problems are tackled via Lagrangian relaxation or column-generation techniques. Righini and Salani and several subsequent works have shown that bounded bidirectional DP algorithms are often superior to their monodirectional counterparts, s…
Discrete Choice Methods with Simulation
2016
Discrete Choice Methods with Simulation by Kenneth Train has been available in the second edition since 2009. The book is published by Cambridge University Press and is also available for download ...
Discrete-mathematical approach to formal description of measurement procedure
1996
The discrete-mathematical model of measurement procedure is developed for facilitating the description of measurements in both quantitative and qualitative scales. On the basis of this model the Measurement Problem is formulated. It is shown that the problem can be considered, in the general case, as one of the discrete optimization problems. The suggested approach brings closer the concepts of a computing algorithm and measurement procedure so that it permits the application of similar tools for the analysis and development of both of them.