Key points are not available for this paper at this time.
The green supply chain is the reduction of the atmospheric release emissions including gases, vapour, smoke, solid or liquid particles.This atmospheric reduction will concern each stage of the chain: supply, production, distribution, warehousing, transport and delivery.The design of this loop is based on industrial ecological perspectives, particularly in the production, and the transport stage.In this work, we present a lotsizing problem with capacitated one warehouse multi retailers (OWMR) under the minimization of particles matter (PM) emission from production and delivery, knowing that the problem is an NP-hard.We have developed a logistics structure containing a production unit connected to a distribution network characterized by (size, number and location) retailers specializing in a single type of product.Then, we will introduce our mathematical problem modelling using mixed-integer programming and develop an approach based on the metaheuristic called binary particle swarm optimization (BPSO) in this approach; we will study new strategies and techniques concerning the particle swarm parameters.The improved BPSO will be tested on a series of benchmark data sets and compared with CPLEX.According to the experimental results, this approach is effective in minimizing the total cost of the supply chain and promoting green technology by reducing the number of the particles emitted into the air.It also provides a decision support system to answer key questions about when and how much produce and distribute in a sustainable environment.
Imen Driss (Wed,) studied this question.