Supply Chain Logistics Network Research Articles

Immune Genetic Algorithm for Supply Chain Logistics Network Optimization Problem

Immune Genetic Algorithm for Supply Chain Logistics Network Optimization Problem

Logistics System Planning Based on Industrial Supply Chain - Yunnan Province as Example

The logistics industry is the integration of transport, warehousing, freight forwarding and information industries, such as a composite service industry, is an important part of the national economy, involving wide areas, absorbing large employment, promoting production and consumption, it is always playing a positive role. Logistics has played an important role in promoting the industry structural adjustment, which can change the mode of economic development and enhance the competitiveness of the national economy. Logistics industry is relying on the industries, through the study of industrial supply chain logistics system architecture model, and submits the corresponding industry-based supply chain logistics network planning model, and propose relevant countermeasures and proposals based on the logistics industry in Yunnan Province as empirical Measure. The study of logistics can be start with three basic levels that is the enterprise logistics, trade logistics, and social logistics, finally to build a highly efficient, integrated logistics system of society. Construction of industrial supply chain logistics system, through the construction of industrial supply chain logistics system so that to integrate the social logistics resources of industry as a whole, to achieve large scale, efficiency, integration, can play a role in promoting socio-economic development .

Optimisation of supply chain logistics network using random search techniques

Fierce market competition is making companies move from their traditional business strategies towards integrated strategic alliances. In order to integrate and manage their business processes like procurement, inventory, manufacturing, logistics and sales, a new technological and quantitative tool is needed. In this paper, a supply chain logistics network model is developed with the objective of minimising the total cost of production and distribution. The Genetic Algorithm (GA) and Particle Swarm (PS) search techniques are proposed for optimising the supply chain logistics network. The computational results of these algorithms are validated with the results obtained using Excel's Solver Optimizer.