JIT Supply Model Under The Short - Haul Combined Transport Optimization Model

With the development of modern logistics and the growth of awareness of logistics management, enterprises put more and more cares on logistics cost. How to decrease logistics cost is a primary aim of enterprise logistics practice.Supply logistics, as a relative independent part of whole production systems, keeps the normal operation by close cooperation with other subsystems such as manufacturing, financial and marketing. Both of maintaining supply and of efficient organization with low cost and high reliability is the basic requirement of supply logistics, so it is a hard task for most of enterprises. How to reduce logistics cost, and increase service level thus implement the whole system optimization become one of the key factors of improving competition ability of manufacturing systems.Short split merge problem in a inbound logistics is studied in this thesis. A combined transportation model is established. Heuristic algorithm based on the best fit decreasing (BFD) and an improved partheno genentic algorithm (PGA) are used to solve this problem separately. Operations cost and efficiency are analyzed respectively. Crossover of traditional GA is not used in PGA thus pre-convergence is avoided in PGA. It has several good characters such as gene replacement, gene inverse so it has it’s special strength in solving difficult optimization problems. A real inbound logistics from an auto industry is used as the simulation example. Numerical results show that PGA has advantages than BFD and TGA. Therefore, the model and algorithm proposed in this paper is effective.