Logistics Scheduling With Batching Delivery And Economic Lot-sizing Problems In Supply Chain Management

In rencent years,supply chain management as a management philosophy has been attraced at home and abroad.Because of the application of operations research and statistical methods,more and more scholars use operations research methods to solve the problem in supply chain management.They reduce practical problems to a mathematical problem,and through the creation of mathematical model to solve the problem.In this thesis,first we study the model of logistics scheduling with batching delivery.Our objective is to minimizing the sum of weighted job delivery time and total transportation cost.Then we study the ELS problem in inventory management.Three chapters are included in this thesis.In the first chapter,some notations,definitions and basic background information about the subject are introduced.In the second chapter,we study the model of logistics scheduling with batching delivery of jobs with release time.Our objective is to minimizing the sum of weighted job delivery time and total transportation cost.The delivery time is the completion time on the processor of the last job of the batch job belongs to plus transportation time.In the model of the number of jobs' release times being constant,we consider two special cases and provide a dynamic programming algorithm for the case of the weighets being agreeable,also,give an optimal algorithm when batching is not allowed.For the general problem,we present an approximation algorithm with a competitive ratio B and analysis its complexity.In the third chapter,we present a two-echelon dynamic lot-sizing model where both dispatch modes have container-based cost structure.Our objective is to find the optimal policy to satisfy all demands at the minimum cost.When the size of a container for one mode is an integer multiple of the size of a container for the other mode,we study the optimality properties of the problem and provide a polynomial algorithm based on a dynamic programming approach.The complexity of the algorithm is O(T~6),in which T is the number of periods in planning horizon.