Adaptive memory artificial

Adaptive memory artificial

 a b s t r a c t

Cross-docking distribution is becoming increasingly prevalent in supply chain management (SCM) due to the replacement of storage and order-picking with efficient product consolidation.

Several successful cross-docking applications have been put into practice by companies such as Wal-Mart, FedEx, and Home Depot.

Cross-docking consists of interrelated operations which require proper synchronization.

Only a few early attempts have ad- dressed the vehicle routing problem in this context.

Moreover, the social consciousness of sustainable development has brought up the issue of green SCM which is not only environment-friendly but also beneficial to business values.

This paper first addresses a previously studied problem and then proposes a new problem version for planning the least cost green vehicle routing in which the deployed vehicles transport the final

 

 

 

 

 

 

 

 

products from suppliers to customers through a cross-dock subject to a CO 2 intensity constraint.

 

 

We develop an adaptive memory artificial bee colony (AMABC) algorithm to tackle both problems.

Compared to a Tabu search proposed in the literature, the AMABC algorithm can reach higher fuel efficiency by managing the loading along the route and yield less cost and CO 2 intensities.

Statistical tests of simulation and geographic data show that the AM- ABC method is robust against the problem size and convergence of the objective value is guaranteed with high confidence.

Concluding remarks

 

 

 

 

 

 

 

 

This paper addresses a new context of vehicle routing for facilitating the green supply chain management with cross- docking. Our new problem compared to previous versions has the following features.

The objective is extended to redefine the operational cost which allows to include vehicle depreciation expense and labor cost, reflecting the practice in transportation business.

The environmental factor, such as CO 2 emission, increasingly affects the business value.

We introduce a CO 2 –limit constraint into our model and enforce the green vehicle routing which considers not only the traveling distance but also the fuel efficiency

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