Recently global companies separate their work process using an outsourcing except for their core parts. This has led them to give more importance to the purchasing function and its associated decisions. And suppliers have to determine when and how many units to order while minimize total ordering costs and inventory holding costs over the finite horizon.
The quantity produced is limited by the machine capacity, and, in order to make full use of work force, it should not be too small. Therefore manufacturers commonly have a minimum order size. It often brings suppliers lost sales, which is unsatisfied demand. In order size problem, it means a lot to consider minimum order size from a point of view of a supplier because it makes problem more realistic.
This research proposes an integer programming model with minimum order size restriction. The objective of this model is to minimize a sum of fixed ordering, item, inventory holding, and lost sale costs. To solve this problem, this research suggests the algorithm and illustrates the algorithm with an example. Finally, computational experiments are conducted to evaluate the solution on randomly generated test instances indicate that the algorithm obtains good solutions with a reasonable solution time.
Chapter 1 Introduction 1
1.1 Background 1
1.2 Research scope 2
Chapter 2 Literature Review 4
2.1 Characteristics of lot sizing models 4
2.2 Classification of the uncapacitated lot sizing problem 6
2.3 Classification of the capacitated lot sizing problem 8
Chapter 3 Dynamic Lot Sizing with Minimum Order Size and Lost Sales 11
3.1 Problem description 11
3.2 Assumptions 12
3.3 Notations 13
3.4 Integer programming model 14
Chapter 4 Methodology 16
4.1 Solution algorithm 16
4.2 Example problem 23
Chapter 5 Computational Experiments 27
5.1 The effect of setup costs 27
5.2 The effect of minimum order sizes 30
5.3 The effect of planning periods 32
Chapter 6 Conclusions 34