Because logistic is a process-oriented business, we propose in this paper a measurement system of decision support for assessing the costs associated with each logistics process. This system allows calculating economic, environmental and social costs of logistics process to ensure a sustainable logistics. We have formulated the problem and we present some simulation for testing our system. This proposition allows the decision-maker to have knowledge of economic, ecological and social cost before making a decision.

In any increasing competitive environment and even in companies; we must adopt a good logistic chain management policy which is the main objective to increase the overall gain by maximizing profits and minimizing costs, including manufacturing costs such as: transaction, transport, storage, etc. In this paper, we propose a cloud platform of this chain logistic for decision support; in fact, this decision must be made to adopt new strategy for cost optimization, besides, the decision-maker must have knowledge on the consequences of this new strategy. Our proposed cloud computing platform has a multilayer structure; this later is contained from a set of web services to provide a link between applications using different technologies; to enable sending; and receiving data through protocols, which should be understandable by everyone. The chain logistic is a process-oriented business; it’s used to evaluate logistics process costs, to propose optimal solutions and to evaluate these solutions before their application. As a scenario, we have formulated the problem for the delivery process, and we have proposed a modified Bin-packing algorithm to improve vehicles loading.

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It has grown quite conspicuous that no company is immune to the increase in fuel prices and energy sources used for air conditioning, refrigeration and heating, as well as traffic congestion and the degradation of road infrastructures. It is for this reason that companies are increasingly concerned about energy and environmental issues and are, therefore, more aware of the need to revise their logistics for the purpose of reducing costs and increasing competitiveness. In order to minimise the energy costs associated with transportation, it is sensical to consider a two-echelon location routing problem (2E-LRP) where two distribution levels are composed of three disjoint sets of nodes corresponding to the depots, the distribution centres and the customers, respectively. For this, we propose a mathematical model, a genetic algorithm, and a dynamic island model to optimise the assignment and the routing of freight. Eventual results show a minimisation of energy cost and CO2 rate.

The development of cloud computing solutions for logistics offers new benefits to companies, such as access to resources on demand, elasticity and usage billing. In this paper, we propose a multi-agent system based on a cloud computing platform called system agent cloud logistics (SACL), which aims to measure the economic, environmental and social performances of a logistic process and to help a company to make the right decision. For achieving this goal, our proposed system integrates: cloud computing technology, web services techniques, multi-agent approach, and simulation model. As a scenario, we've chosen the case of a virtual pharmaceutical wholesaler, and we have formulated the problem for command preparation process. The results show that our proposed system helps the decision maker to estimate the economic, environmental and social costs of a logistic process and to know the impact of a new strategic solution and its cost before retaining it.