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An evolutionary algorithm for optimizing material flow in supply chains

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TLDR
In this article, an evolutionary algorithm (EA) is proposed for optimal synchronization of supply chains, which is shown to be much faster at solving large problems than an enumeration procedure and exhibits robust behavior when tested on a variety of different problem parameters.
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This article is published in Computers & Industrial Engineering.The article was published on 2002-09-01 and is currently open access. It has received 70 citations till now. The article focuses on the topics: Supply chain & Evolutionary algorithm.

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Citations
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Journal ArticleDOI

Use of genetic algorithms to solve production and operations management problems: A review

TL;DR: A review of the use of genetic algorithms to solve operations problems and the designs of the genetic algorithms used to solve them is provided.
Journal ArticleDOI

Genetic algorithms for supply-chain scheduling: A case study in the distribution of ready-mixed concrete

TL;DR: This paper proposes a novel meta-heuristic approach based on a hybrid genetic algorithm combined with constructive heuristics for ready-mixed concrete delivery of just-in-time production and transportation to distributed customers.
Journal ArticleDOI

Literature review of JIT-KANBAN system

TL;DR: In this paper, a survey of the JIT-Kanban literature is presented, focusing on the philosophy of JIT, and the concept involved in the push and pull system.
Journal ArticleDOI

A hybrid genetic algorithm for the finite horizon economic lot and delivery scheduling in supply chains

TL;DR: A new mixed integer nonlinear program (MINLP) and an optimal enumeration method to solve the lot and delivery scheduling problem in a simple supply chain where a single supplier produces multiple components on a flexible flow line (FFL) and delivers them directly to an assembly facility (AF).
Journal ArticleDOI

Optimal design methodologies for configuration of supply chains

TL;DR: In this article, the authors describe a methodology developed for designing an optimal configuration for a supply chain, which consists of a model builder coupled with two optimisation algorithms that automatically build a sequence of configurations that systematically move towards an optimum design.
References
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Book

Genetic Algorithms + Data Structures = Evolution Programs

TL;DR: GAs and Evolution Programs for Various Discrete Problems, a Hierarchy of Evolution Programs and Heuristics, and Conclusions.
Book

Introduction to sequencing and scheduling

A. J. Clewett
TL;DR: In this article, the authors present an introduction to Sequencing and Scheduling in the context of the Operational Research Society (ORS) and the International Journal of Distributed Sensor Networks (ILS).
Book

Introduction to Supply Chain Management

TL;DR: The role of information systems and technology in supply chain management is discussed in this article, where a conceptual model of alliance development is presented to develop a trusting relationship with partners in the supply chain and resolve conflicts in a supply chain relationship.
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