A Novel Hybrid Fuzzy Multi-objective Linear Programming Method of Aggregate Production Planning

Abstract

In this work a novel fuzzy multi-objective linear programming (FMOLP) method based on hybrid fuzzy inference systems is proposed for solving the general framework of integration of self-contained assembly unit in a fuzzy environment where the product price, unit cost of not utilization of resources, work force level, production capacity and market demands are fuzzy in nature. The proposed model attempts to minimize total production costs, maximizing the shop floor resources utilization and the profits, considering inventory level, and capacity. Pareto solutions optimization is computed with different techniques and results are presented and discussed with interesting practical implications.

Aggregate production planning: A literature review and future research directions

“…Deterministic Single Aghezzaf & Artiba, 1998;Silva & JoÄOoisboa, 2000;Pradenas & Pe˜nailillo, 2004;Fahimnia et al, 2005;Pipery & Vachony, 2001;Singhvi & Shenoy, 2002;Techawiboonwong & Yenradee, 2003;Mazzola et al, 1998;Sillekens et al, 2011;Zhang et al, 2012;Ramezanian et al, 2012;Chaturvedi & Bandyopadhyay, 2015;Chaturvedi, 2017Multiple Leung & Chan, 2009Leung et al, 2003;Chakrabortty & Akhtar Hasin, 2013;Entezaminia et al, 2016;Abu Bakar et al, 2016;Mehdizadeh et al, 2018 Uncertain Fuzzy Single Baykasoglu, 1999;Wang & Fang, 2000;Fung et al, 2003;Tang et al, 2000;Tang et al, 2003;Ning et al, 2006;Aliev et al, 2007;Chen & Huang, 2010;Iris & Cevikcan, 2014;Rahmani et al, 2014;Chakrabortty et al, 2015Multiple Wang & Fang, 1997Baykasoglu & Gocken, 2006;Sakallı et al, 2010;Baykasoglu & Gocken, 2010;Sadeghi et al, 2013;da Silva & Silva Marins, 2014;Gholamian et al, 2016;Fiasché et al, 2016;Chauhan et al, 2017;…”

Evaluating the performance of aggregate production planning strategies under uncertainty in soft drink industry

“…Since APP problem always involves several criteria (objectives) and due to the vagueness of the available information, fuzzy multi-objective programming has been widely used in this area. Lee (1990), Gen, Tsujimura and Ida (1992), Wang and Fang (2001), Wang and Liang (2004), Ghasemy Yaghin, Torabi and Fatemi Ghomi (2012), Madadi and Wong (2014), Gholamian et al (2015), Gholamian, Mahdavi and Tavakkoli-Moghaddam (2016), Kalaf et al (2015), Sisca, Fiasché and Taisch (2015), Fiasché et al (2016) and Zaidan et al (2017) utilised various kinds of fuzzy multi-objective optimisation models to study APP under uncertainty. Gholamian et al (2015) and Gholamian, Mahdavi and Tavakkoli-Moghaddam (2016) developed a fuzzy multi-site multi-objective mixed integer nonlinear APP model in a supply chain under uncertainty with fuzzy demand, fuzzy cost parameters, etc.…”

“…are supposed to be fuzzy variables. Fiasché et al (2016) developed a fuzzy linear multi-objective optimisation model of APP in fuzzy environment where the product price, unit cost of not utilising the resources, etc. are of fuzzy nature.…”

Impact of Forecasting Techniques and Market Demand Scenarios on Multi-Product, Multi-Period Aggregate Production Planning

“…Gholamian, et al [24] formulated fuzzy multiobjective mixed integer nonlinear programming where they focused on four conflicting objectives such as minimizing total cost and fluctuations in the rate of changes of the workforce and maximizing customer satisfaction and the total value of purchasing. Another hybrid fuzzy interference system is proposed by Fiasché, et al [25] where they computed Pareto solutions optimization with two different techniques.…”