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Aggregate planning through the imprecise goal programming model: integration of the manager's preferences
Author(s) -
Mezghani Mouna,
Loukil Taicir,
Aouni Belaïd
Publication year - 2012
Publication title -
international transactions in operational research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.032
H-Index - 52
eISSN - 1475-3995
pISSN - 0969-6016
DOI - 10.1111/j.1475-3995.2012.00844.x
Subject(s) - aggregate planning , aggregate (composite) , time horizon , computer science , production planning , production (economics) , operations research , goal programming , plan (archaeology) , set (abstract data type) , range (aeronautics) , industrial engineering , mathematical optimization , economics , engineering , mathematics , microeconomics , programming language , materials science , archaeology , aerospace engineering , composite material , history
Aggregate planning involves planning the best quantity to be produced during time periods in the medium‐range horizon at the lowest cost. Usually, the production manager seeks a plan that simultaneously optimizes several incommensurable and conflicting objectives, such as total cost, level of inventories, level of customer service, fluctuation in workforce, and utilization level of the physical facility and equipment. The goal programming (GP) model is one of the best known multi‐objective programming models that considers simultaneously several conflicting objectives to select the most satisfactory solution among a set of feasible solutions. In the production planning problem, the goals and the technological parameters are naturally imprecise. Moreover, the existing GP formulations developed in industrial engineering and aggregate production planning do not explicitly incorporate the manager's preferences. The aim of this paper is to develop a GP formulation within an imprecise environment where the concept of satisfaction function will be utilized to explicitly introduce the manager's preferences into the aggregate planning model.