81,458 research outputs found
Facility layout problem: Bibliometric and benchmarking analysis
Facility layout problem is related to the location of departments in a facility area, with the aim of determining the most effective configuration. Researches based on different approaches have been published in the last six decades and, to prove the effectiveness of the results obtained, several instances have been developed. This paper presents a general overview on the extant literature on facility layout problems in order to identify the main research trends and propose future research questions. Firstly, in order to give the reader an overview of the literature, a bibliometric analysis is presented. Then, a clusterization of the papers referred to the main instances reported in literature was carried out in order to create a database that can be a useful tool in the benchmarking procedure for researchers that would approach this kind of problems
Learning behavior in abstract memory schemes for dynamic optimization problems
This is the post-print version of this article. The official article can be accessed from the link below - Copyright @ 2009 Springer VerlagIntegrating memory into evolutionary algorithms is one major approach to enhance their performance in dynamic environments. An abstract memory scheme has been recently developed for evolutionary algorithms in dynamic environments, where the abstraction of good solutions is stored in the memory instead of good solutions themselves to improve future problem solving. This paper further investigates this abstract memory with a focus on understanding the relationship between learning and memory, which is an important but poorly studied issue for evolutionary algorithms in dynamic environments. The experimental study shows that the abstract memory scheme enables learning processes and hence efficiently improves the performance of evolutionary algorithms in dynamic environments.The work by S. Yang was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1
Decomposition by Successive Convex Approximation: A Unifying Approach for Linear Transceiver Design in Heterogeneous Networks
We study the downlink linear precoder design problem in a multi-cell dense
heterogeneous network (HetNet). The problem is formulated as a general
sum-utility maximization (SUM) problem, which includes as special cases many
practical precoder design problems such as multi-cell coordinated linear
precoding, full and partial per-cell coordinated multi-point transmission,
zero-forcing precoding and joint BS clustering and beamforming/precoding. The
SUM problem is difficult due to its non-convexity and the tight coupling of the
users' precoders. In this paper we propose a novel convex approximation
technique to approximate the original problem by a series of convex
subproblems, each of which decomposes across all the cells. The convexity of
the subproblems allows for efficient computation, while their decomposability
leads to distributed implementation. {Our approach hinges upon the
identification of certain key convexity properties of the sum-utility
objective, which allows us to transform the problem into a form that can be
solved using a popular algorithmic framework called BSUM (Block Successive
Upper-Bound Minimization).} Simulation experiments show that the proposed
framework is effective for solving interference management problems in large
HetNet.Comment: Accepted by IEEE Transactions on Wireless Communicatio
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