Just-in-time production and delivery in supply chains: a hybrid evolutionary approach

The timely production and distribution of rapidly perishable goods is one of the most challenging logistic problems in the context of supply chain operation. The problem involves several tightly interrelated planning, scheduling and routing problems, each with large combinatorial complexity. From a...

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Vydáno v:2004 IEEE International Conference on Systems, Man and Cybernetics Ročník 2; s. 1932 - 1937 vol.2
Hlavní autoři: Naso, D., Surico, M., Turchiano, B., Kaymak, U.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: Piscataway NJ IEEE 2004
Témata:
Applied sciences
Cement industry
Computer science; control theory; systems
Concrete
Control theory. Systems
Evolutionary computation
Exact sciences and technology
Genetic algorithms
Job shop scheduling
Logistics
Operational research and scientific management
Operational research. Management science
Production
Routing
Scheduling, sequencing
Supply chain management
Supply chains
Constructive mathematics
Combinatorial problem
Evolutionary algorithm
Routing
Scheduling
Combinatorial optimization
Delivery lead time
Return on investment
Genetic algorithm
Just in time
Heuristic approach
Planning
Logistics
ISBN:0780385667, 9780780385665
ISSN:1062-922X
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Shrnutí:The timely production and distribution of rapidly perishable goods is one of the most challenging logistic problems in the context of supply chain operation. The problem involves several tightly interrelated planning, scheduling and routing problems, each with large combinatorial complexity. From a more practical perspective, the problem calls for a trade-off between risks and returns. To effectively deal with these considerable difficulties, we propose a novel meta-heuristic approach based on a hybrid evolutionary algorithm combined with constructive heuristics for addressing just-in-time production and delivery with time constraints on both the earliness and the lateness of supply. Distribution of ready-made concrete is used as a practical example. A case study based on industrial data illustrates the potential of the proposed approach.
ISBN:0780385667
9780780385665
ISSN:1062-922X
DOI:10.1109/ICSMC.2004.1399968