Abstract
Our research focuses on the development of two cooperative approaches for resolution of the multi-item capacitated lot-sizing problems with time windows and setup times (MICLSP-TW-ST). In this paper we combine variable neighborhood search and accurate mixed integer programming (VNS-MIP) to solve MICLSP-TW-ST. It concerns so a particularly important and difficult problem in production planning. This problem is NP-hard in the strong sense. Moreover, it is very difficult to solve with an exact method; it is for that reason we have made use of the approximate methods. We improved the variable neighborhood search (VNS) algorithm, which is efficient for solving hard combinatorial optimization problems. This problem can be viewed as an optimization problem with mixed variables (binary variables and real variables). The new VNS algorithm was tested against 540 benchmark problems. The performance of most of our approaches was satisfactory and performed better than the algorithms already proposed in the literature.
Highlights
Introduction and MotivationsThe multi-item capacitated lot-sizing problem with time windows and setup times (MICLSP-TW-ST) has been an important part of material requirement planning (MRP) system
Our research focuses on the development of two cooperative approaches for resolution of the multi-item capacitated lot-sizing problems with time windows and setup times (MICLSP-TW-ST)
That is why we made recourse to the time window constraint and its importance in modeling and solving production planning problems, and in this case one should consider for each request an availability date in addition to her delivery date
Summary
The multi-item capacitated lot-sizing problem with time windows and setup times (MICLSP-TW-ST) has been an important part of material requirement planning (MRP) system. That is why we made recourse to the time window constraint and its importance in modeling and solving production planning problems, and in this case one should consider for each request an availability date in addition to her delivery date. Dauzère-Pérès et al [9] are the first ones who presented the production time windows constraint in the LSP context They have treated the customer specific case with single item. Karimi et al [13] and Dauzère-Pérès & Nordli [9] have proven that the algorithmic complexity for the lot sizing problem to a product as well as without capacity constraint with noncustomer specific is NP-complete.
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