Green Lot-Sizing

MJ (Mathijn Retel) Retel Helmrich

Research output: Types of ThesisDoctoral ThesisInternal

Abstract

The lot-sizing problem concerns a manufacturer that needs to solve a production planning problem. The producer must decide at which points in time to set up a production process, and when he/she does, how much to produce. There is a trade-off between inventory costs and costs associated with setting up the production process at some point in time. Traditionally, the lot-sizing model focuses solely on cost minimisation. However, production decisions also affect the environment in many ways. In this dissertation, the classic lot-sizing model is extended into several different directions, in order to take various environmental considerations into account. First, items that are returned from customers are included in the lot-sizing problem, within the context of reverse logistics. These items can be remanufactured to fulfil customer demand. In another extension, a minimum is imposed on the size of a production batch, in order to reduce the pollution associated with producing many small batches. Furthermore, a lot size model is considered in which there is a maximum on the amount of pollutants, such as carbon dioxide. This model can also be seen as a bi-objective lot-sizing problem. The mathematical models that arise from these extensions are fundamentally harder to solve than the classic lot-sizing problem. Several approaches to solving these problems are developed, based on mathematical optimisation techniques such as mixed integer programming, dynamic programming and fully polynomial time approximation schemes.
Original languageEnglish
Awarding Institution
  • Erasmus University Rotterdam
Supervisors/Advisors
  • Wagelmans, Albert, Supervisor
  • Dauzere-Peres, Doctoral committee member
  • Dekker, Rommert, Doctoral committee member
  • van de Velde, Steef, Doctoral committee member
  • van den Heuvel, Wilco, Co-supervisor
  • Jans, Co-supervisor
Award date3 Oct 2013
Place of PublicationRotterdam
Print ISBNs9789058923424
Publication statusPublished - 3 Oct 2013

Research programs

  • EUR ESE 31
  • EUR ESE 32
  • RSM LIS

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