Due to the repetitive nature of inventory planning over the planning horizon, the operator in charge has to perform planning tasks repetitively, and consequently s/he becomes more familiar with the tasks over time. Familiarity with the tasks suggests that learning takes place in inventory planning. Even though the operator’s learning over time might improve his/her efficiency, prior research on fuzzy lot-sizing problems mostly overlooked the effect of human learning in their models and its impact on the operator’s performance. To close the research gap in this area, this paper models the operator's learning in a fuzzy economic order quantity model with backorders. The paper models a situation where the operator applies the acquired knowledge over the cycles in setting the fuzzy parameters at the beginning of every planning cycle, where his/her learning ability includes the cognitive and motor capabilities of a human being. Subsequently, a mathematical model which takes account of a two-stage human learning over the planning cycles is developed, which is then analytically investigated using sample data-sets. The results indicate that both operator’s capabilities, cognitive and motor, affect the efficiency of the fuzzy lot-sizing inventory model, but the influence of the cognitive capability is more profound, which in turn suggests the importance of training programmes for the workforces. The results of the sensitivity analysis also draw some managerial insights for the case that some model parameters vary over the planning horizon.

A fuzzy lot-sizing problem with two-stage composite human learning / Nima, Kazemi; S., Abdul Rashid; Ehsan, Shekarian; Bottani, Eleonora; Montanari, Roberto. - In: INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH. - ISSN 1366-588X. - 54:16(2016), pp. 5010-5025. [10.1080/00207543.2016.1165874]

A fuzzy lot-sizing problem with two-stage composite human learning

BOTTANI, Eleonora;MONTANARI, Roberto
2016

Abstract

Due to the repetitive nature of inventory planning over the planning horizon, the operator in charge has to perform planning tasks repetitively, and consequently s/he becomes more familiar with the tasks over time. Familiarity with the tasks suggests that learning takes place in inventory planning. Even though the operator’s learning over time might improve his/her efficiency, prior research on fuzzy lot-sizing problems mostly overlooked the effect of human learning in their models and its impact on the operator’s performance. To close the research gap in this area, this paper models the operator's learning in a fuzzy economic order quantity model with backorders. The paper models a situation where the operator applies the acquired knowledge over the cycles in setting the fuzzy parameters at the beginning of every planning cycle, where his/her learning ability includes the cognitive and motor capabilities of a human being. Subsequently, a mathematical model which takes account of a two-stage human learning over the planning cycles is developed, which is then analytically investigated using sample data-sets. The results indicate that both operator’s capabilities, cognitive and motor, affect the efficiency of the fuzzy lot-sizing inventory model, but the influence of the cognitive capability is more profound, which in turn suggests the importance of training programmes for the workforces. The results of the sensitivity analysis also draw some managerial insights for the case that some model parameters vary over the planning horizon.
A fuzzy lot-sizing problem with two-stage composite human learning / Nima, Kazemi; S., Abdul Rashid; Ehsan, Shekarian; Bottani, Eleonora; Montanari, Roberto. - In: INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH. - ISSN 1366-588X. - 54:16(2016), pp. 5010-5025. [10.1080/00207543.2016.1165874]
File in questo prodotto:
File Dimensione Formato  
2016 A fuzzy lot_IJPR_54(16)_5010–5025.pdf

solo utenti autorizzati

Descrizione: Articolo principale
Tipologia: Versione (PDF) editoriale
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 718.96 kB
Formato Adobe PDF
718.96 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
A fuzzy lot_IJPR_54(16)_5010–5025 (1).pdf

accesso aperto

Tipologia: Documento in Post-print
Licenza: Creative commons
Dimensione 1.63 MB
Formato Adobe PDF
1.63 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2808748
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 23
  • ???jsp.display-item.citation.isi??? 16
social impact