چكيده به لاتين
The current study addresses a joint order acceptance and integrated production-distribution scheduling, lot streaming in a flexible flow shop and batch delivery considering third-party logistics in which the transportation fleet is limited.
To do so, firstly, it is necessary to investigate the problem in simpler conditions and to analyze its properties. In the first problem, the order acceptance is considered in an integrated production-distribution scheduling with the single machine in the production environment and batch delivery in the distribution. In the second problem, the same problem is considered with considering the transportation fleet limitation and using the third-party logistics companies. Then, in the final problem, the joint order acceptance and integrated production-distribution scheduling with a flexible flow shop production enviorement, lot streaming production technique and batch delivery is addressed. In this problem, the transportation fleet is limited and the company can use the third party logistics, too. The results of this study it has been used in real industry related to the production and distribution of yoghurt dairy industry.
In studying the first and second problem, the optimal properties of the problem is extracted, a nonlinear integer programming is proposed which has been transformed into a linear integer programming using mathematical techniques. To solve each of the problems, a branch and bound algorithm has been developed in which the branching is based on the optimality properties of the problem. Given the complexity of the problems, to solve the large-scale test problems, a genetic algorithm has been developed in which four heuristic algorithms are presented to generate the initial solution and also a local search algorithm is proposed.
In both cases, by generating test problems, the verification and the performance of mathematical model, branch and bound algorithms, and metaheuristic algorithms is investigated. The results show that for the test problems of small size, the branch and bound algorithm results an optimal solution with considerably less time than Lingo's software. Also, sensitivity analysis shows performing the order acceptance will increase the total net profit.
Subsequently, according to the conditions in the case study of the yoghurt production line and distribution of it in the Kalleh dairy company, this research is developed for a flexible flow shop production environment with lot streaming technique. For this, a linear integer programming model and a hybrid genetic algorithm with a restart phase and a local search is presented. The proposed model and algorithm are solved based on test problems. Then, the effect of its implementation based on the parameters and items of the yoghurt production line and distribution in the Kalleh dairy company has been investigated. Comparing the presented algorithm with the company's implementation plan shows an improvement of 13% in the profit. The results show that the most reduced costs using the proposed algorithm are related to the cost of set up and CIP.
