48,697 research outputs found
The Project Scheduling Problem with Non-Deterministic Activities Duration: A Literature Review
Purpose: The goal of this article is to provide an extensive literature review of the models and solution procedures proposed by many researchers interested on the Project Scheduling Problem with nondeterministic activities duration. Design/methodology/approach: This paper presents an exhaustive literature review, identifying the existing models where the activities duration were taken as uncertain or random parameters. In order to get published articles since 1996, was employed the Scopus database. The articles were selected on the basis of reviews of abstracts, methodologies, and conclusions. The results were classified according to following characteristics: year of publication, mathematical representation of the activities duration, solution techniques applied, and type of problem solved. Findings: Genetic Algorithms (GA) was pointed out as the main solution technique employed by researchers, and the Resource-Constrained Project Scheduling Problem (RCPSP) as the most studied type of problem. On the other hand, the application of new solution techniques, and the possibility of incorporating traditional methods into new PSP variants was presented as research trends. Originality/value: This literature review contents not only a descriptive analysis of the published articles but also a statistical information section in order to examine the state of the research activity carried out in relation to the Project Scheduling Problem with non-deterministic activities duration.Peer Reviewe
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
Tackling Dynamic Vehicle Routing Problem with Time Windows by means of Ant Colony System
The Dynamic Vehicle Routing Problem with Time Windows (DVRPTW) is an
extension of the well-known Vehicle Routing Problem (VRP), which takes into
account the dynamic nature of the problem. This aspect requires the vehicle
routes to be updated in an ongoing manner as new customer requests arrive in
the system and must be incorporated into an evolving schedule during the
working day. Besides the vehicle capacity constraint involved in the classical
VRP, DVRPTW considers in addition time windows, which are able to better
capture real-world situations. Despite this, so far, few studies have focused
on tackling this problem of greater practical importance. To this end, this
study devises for the resolution of DVRPTW, an ant colony optimization based
algorithm, which resorts to a joint solution construction mechanism, able to
construct in parallel the vehicle routes. This method is coupled with a local
search procedure, aimed to further improve the solutions built by ants, and
with an insertion heuristics, which tries to reduce the number of vehicles used
to service the available customers. The experiments indicate that the proposed
algorithm is competitive and effective, and on DVRPTW instances with a higher
dynamicity level, it is able to yield better results compared to existing
ant-based approaches.Comment: 10 pages, 2 figure
Solving Factored MDPs with Hybrid State and Action Variables
Efficient representations and solutions for large decision problems with
continuous and discrete variables are among the most important challenges faced
by the designers of automated decision support systems. In this paper, we
describe a novel hybrid factored Markov decision process (MDP) model that
allows for a compact representation of these problems, and a new hybrid
approximate linear programming (HALP) framework that permits their efficient
solutions. The central idea of HALP is to approximate the optimal value
function by a linear combination of basis functions and optimize its weights by
linear programming. We analyze both theoretical and computational aspects of
this approach, and demonstrate its scale-up potential on several hybrid
optimization problems
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A memetic ant colony optimization algorithm for the dynamic travelling salesman problem
Copyright @ Springer-Verlag 2010.Ant colony optimization (ACO) has been successfully applied for combinatorial optimization problems, e.g., the travelling salesman problem (TSP), under stationary environments. In this paper, we consider the dynamic TSP (DTSP), where cities are replaced by new ones during the execution of the algorithm. Under such environments, traditional ACO algorithms face a serious challenge: once they converge, they cannot adapt efficiently to environmental changes. To improve the performance of ACO on the DTSP, we investigate a hybridized ACO with local search (LS), called Memetic ACO (M-ACO) algorithm, which is based on the population-based ACO (P-ACO) framework and an adaptive inver-over operator, to solve the DTSP. Moreover, to address premature convergence, we introduce random immigrants to the population of M-ACO when identical ants are stored. The simulation experiments on a series of dynamic environments generated from a set of benchmark TSP instances show that LS is beneficial for ACO algorithms when applied on the DTSP, since it achieves better performance than other traditional ACO and P-ACO algorithms.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/01 and Grant EP/E060722/02
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