Future paths for integer programming and links to artificial intelligence
TLDR
Four key areas of Integer programming are examined from a framework that links the perspectives of artificial intelligence and operations research, and each has characteristics that appear usefully relevant to developments on the horizon.About:
This article is published in Computers & Operations Research.The article was published on 1986-05-01 and is currently open access. It has received 3985 citations till now. The article focuses on the topics: Integer programming & Tabu search.read more
Citations
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Territory-Based Vehicle Routing in the Presence of Time-Window Constraints
TL;DR: A two-phase TBRA is developed and it is found that the consideration of geographical aspects in the districting is paramount for generating high-quality territories, whereas explicitly incorporating time window characteristics and historical demand data does not lead to a perceptible improvement of the solution quality.
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Hybrid cuckoo search optimization algorithms applied to complex wellbore trajectories aided by dynamic, chaos-enhanced, fat-tailed distribution sampling and metaheuristic profiling
TL;DR: Several configurations of the hCSO are shown to work efficiently in locating the global optimum, avoiding being trapped by the many local optima within the solution space, requiring less computational time than six other evolutionary algorithms evaluated with the same number of iterations and population of generated solutions.
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An efficient matheuristic for the robust multiple allocation p-hub median problem under polyhedral demand uncertainty
TL;DR: Extensive computational experiments are conducted based on three well-known data sets in the hub location literature and the results show the capability of the proposed solution algorithm to obtain the optimal solutions in short computational times.
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Metaheuristic profiling to assess performance of hybrid evolutionary optimization algorithms applied to complex wellbore trajectories
TL;DR: Metaheuristic profiling is proposed as an effective technique with which to evaluate the relative contributions of the metaheuristic components of hybrid evolutionary optimization algorithms in progressing searches of feasible solution spaces to locate global optimum values of their objective functions.
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Graph theoretic relaxations of set covering and set partitioning problems
Elia El-Darzi,Gautam Mitra +1 more
TL;DR: Three graph theoretic relaxations of the set covering problem (SCP) and the set partitioning problem (SSP) are reviewed: a network relaxation which can be solved by the greedy method, a matching relaxation and a graph covering relaxation.
References
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Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
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Equation of state calculations by fast computing machines
TL;DR: In this article, a modified Monte Carlo integration over configuration space is used to investigate the properties of a two-dimensional rigid-sphere system with a set of interacting individual molecules, and the results are compared to free volume equations of state and a four-term virial coefficient expansion.
Book
The Sciences of the Artificial
TL;DR: A new edition of Simon's classic work on artificial intelligence as mentioned in this paper adds a chapter that sorts out the current themes and tools for analyzing complexity and complex systems, taking into account important advances in cognitive psychology and the science of design while confirming and extending Simon's basic thesis that a physical symbol system has the necessary and sufficient means for intelligent action.
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Combinatorial optimization: algorithms and complexity
TL;DR: This clearly written, mathematically rigorous text includes a novel algorithmic exposition of the simplex method and also discusses the Soviet ellipsoid algorithm for linear programming; efficient algorithms for network flow, matching, spanning trees, and matroids; the theory of NP-complete problems; approximation algorithms, local search heuristics for NPcomplete problems, more.
Book
The Architecture of Cognition
TL;DR: Adaptive Control of Thought (ACT*) as mentioned in this paper is a theory of the basic principles of operation built into the cognitive system and is the main focus of Anderson's theory of cognitive architecture.