Traditional heuristic versus Hopfield neural network approaches to a car sequencing problem

DOI10.1016/0377-2217(96)00040-9zbMath0912.90165OpenAlexW2005960525WikidataQ62033484 ScholiaQ62033484MaRDI QIDQ1268163

Kate A. Smith, Marimuthu Palaniswami, Mohan Krishnamoorthy

Publication date: 25 May 1999

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0377-2217(96)00040-9

zbMATH Keywords

heuristicsNP-hardHopfield neural networkcar sequencingassembly line

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Deterministic scheduling theory in operations research (90B35) Production models (90B30) Combinatorial optimization (90C27)

Related Items (14)

A hybrid neural approach to combinatorial optimization ⋮ Metaheuristics: A bibliography ⋮ Genetic Algorithm with Hybrid Integer Linear Programming Crossover Operators for the Car-Sequencing Problem ⋮ A heuristic procedure for the automobile assembly-line sequencing problem considering multiple product options ⋮ Iterated tabu search for the car sequencing problem ⋮ Sequencing jobs on a single machine: A neural network approach ⋮ Solving real car sequencing problems with ant colony optimization ⋮ Sequencing mixed-model assembly lines: survey, classification and model critique ⋮ Formulating and solving production planning problems ⋮ Traditional heuristic versus Hopfield neural network approaches to a car sequencing problem ⋮ A review of Hopfield neural networks for solving mathematical programming problems ⋮ Neural networks in business: Techniques and applications for the operations researcher ⋮ A bibliography of neural network business applications research: 1994--1998 ⋮ Heuristic procedure neural networks for the CMST problem

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