Research On Inventory Routing Problem Under Supply Chain

What is the beneficial source of supply chain management for enterprises? To reduce cost.Inventory and transportation cost are two main components of enterprises and the whole supply chain cost. Undoubtedly, to reduce inventory and transportation cost has become one important source of acquiring competitive advantage in supply chain. Generally, to achieve the goal of reducing these supply chain costs is conflicting. Moreover, it is difficult not only to single enterprise, but even to multi-echelon supply chain enterprises. Thus it is one of hot and difficult problems in supply chain management research.This thesis studies series of related research on three-echelon integration and non-integration Inventory Routing Problem under supply chain, which is composed of suppliers, manufacturers and retailers. The main research contents in this thesis can be summarized as follows.1. As to supplier-core supply chain SIRP, this thesis not only constructs the One-Many-Many supply chain models from five dimensions which is periods, vehicles, market demand, market condition and inventory strategies, etc. but also gives the corresponding algorithm.At the beginning, this thesis constructs inventory routing problem models under various dimension scenarios on the basis of storage cost, stockout cost, vehicle routing constant cost, transportation cost, no-load cost, loading/ unloading cost and series of related constraints.On this basis, as to inventory routing problem models under various dimension scenarios, this thesis skillfully implements the transform about storage cost, stockout cost and prior-unit transportation cost by introducing 0-1 integer variables and vehicle routing order variables, which improves the feasibility of model-solving to some extent. Moreover, as to periods scenarios, this thesis solves single-period models by modified ant colony heuristic algorithm and analyses instances optimization results, while multi-period models including single-stage and multi-stage by genetic algorithm. As to vehicles scenarios, this thesis first develops three transportation mode(direct distribution mode, serial routing mode and parallel routing mode), and then analyses some corresponding instances. As to market demand scenarios, this thesis constructs continuous stochastic demand models, such as uniform distribution and normal distribution, and optimizes some instances. In addition, this thesis proposes the principle of "To optimize route under determined demand; while inventory under stochastic demand." in order to facilitate the problem of multi-period inventory routing problem. As to market condition scenarios, this thesis implements market partitioning by modified Voronoi diagram in GIS and cost differential minimum insertion partitioning algorithm. As to inventory strategies scenarios, this thesis compares and analyses supply chain modes between VMI and JMI, which acquires some instance conclusions.2. Similarly, as to manufacturers(retailers)-core supply chain MIRP(RIRP), this thesis not only constructs Many-One-Many(Many-Many-One)supply chain models under various dimensions scenarios on the basis of storage cost, stockout cost, vehicle routing constant cost, transportation cost, no-load cost, loading/unloading cost and series of related constraints, but also gives the corresponding algorithm or instances optimization. These models refer to five dimensions which is periods, vehicles, market demand, market condition and inventory strategies, etc.3. After the research on integrated supply chain Inventory Routing Problem, this thesis studies non-integrated supply chain Inventory Routing Problem in order to achieve "The invisible hand"-supply chain coordination.This thesis studies supply chain return contract under four supply chain transportation modes(SM supply chain, SR supply chain, MM supply chain and MR supply chain), respectively, which consists of a single supplier, a single manufacturer and a single retailer. In conclusion, this thesis proposes supply chain tripartite return contract and its parameters are transportation selection factor, optimal order quantity factor, and profit-sharing factor. Finally, related numerical and conclusion analysis are carried out refers to this contract.