NDLI: An efficient algorithm to solve a multi-objective robust aggregate production planning in an uncertain environment

Content Provider	Springer Nature Link
Author	Al e Hashem, Seyed Mohamad Javad Mirzapour Aryanezhad, Mir Bahador Sadjadi, Seyed Jafar
Copyright Year	2011
Abstract	Risk is inherent in most economic activities. This is especially true of production activities where results of decisions made today may have many possible different outcomes depending on future events. Since companies cannot usually protect themselves completely against risk, they have to manage it. In this paper, we present a multi-objective model to deal with a multi-period multi-product multi-site aggregate production planning problem for a medium-term planning horizon under uncertainty. The first objective function attempts to minimize sum of the expected value and the variability of total costs with reference to inventory levels, regular, overtime and subcontracting levels, backordering levels, and labor, machine and warehouse capacities. The second objective function highlighted the concept of customer service level through minimizing the expected value of maximum shortages among all customers’ zones from which the variability of that is conducted. The last objective function aims to maximize workers productivity, a weighted average of productivity levels in all factories and in all periods which is weighted by the number of k-level labors. Then, we use an efficient algorithm that is a combination of an augmented ε-constraint method and genetic algorithm to solve our proposed model. The results demonstrate the practicability of the proposed multi-objective stochastic model as well as the proposed algorithm.
Starting Page	765
Ending Page	782
Page Count	18
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	58
Issue Number	5-8
e-ISSN	14333015
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-06-03
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Aggregate production planning Stochastic optimization Augmented ε-constraint Genetic algorithm Multi-objective optimization Supply chain management Production/Logistics/Supply Chain Computer-Aided Engineering (CAD, CAE) and Design Mechanical Engineering Industrial and Production Engineering
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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