An interactive decision support system for an aggregate production planning model based on multiple criteria mixed integer linear programming

Carlos Gomes da Silvaa, José Figueirab,c, João Lisboab,d,∗, Samir Barmane

aLeiria Polytechnic School of Technology and Management, Alto do Vieiro, Morro do Lena, 2401-951 Leiria, Portugal

bSchool of Economics, University of Coimbra, Av. Dias da Silva, 165, 3004-512 Coimbra, Portugal

cLAMSADE, University of Paris-Dauphine, Place du Maréchal De Lattre de Tassigny, 75 775 Paris, Cedex 16, France

dInstituto de Sistemas e Robótica, University of Coimbra, Pinhal de Marrocos, Polo II, Portugal

ePrice College of Business, University of Oklahoma, 307 W. Brooks, Norman, OK 73019, USA

Received 25 July2002; accepted 24 August 2004

MRPII 02

Abstract

In this paper, we present an aggregate production planning (APP) model applied to a Portuguese firm that produces construction materials.A multiple criteria mixed integer linear programming (MCMILP) model is developed with the following performance criteria: (1) maximize profit, (2) minimize late orders, and (3) minimize work force level changes. It includes

certain operational features such as partial inflexibilityof the work force, legal restrictions on workload, work force size (workers to be hired and downsized), workers in training, and production and inventorycapacity .

The purpose is to determine the number of workers for each worker type, the number of overtime hours, the inventory level for each product category, and the level of subcontracting in order to meet the forecasted demand for a planning period of 12 months.

Additionally, a decision support system (DSS) based on the MCMILP model is proposed. It will help practitioners find the “best” solution for an APP problem without having to familiarize themselves with the mathematical complexities associated with the model.

An example to illustrate the use of the DSS is also included.  2004 Elsevier Ltd. All rights reserved.

Keywords: Production management; Aggregate planning; Multiple criteria model; Interactive approach; Decision support systems