Volume 31, Issue 2 (IJIEPR 2020)                   IJIEPR 2020, 31(2): 203-215 | Back to browse issues page

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Fattahi P, Tanhatalab M, Motavallian J, Karimi M. An optimization model based decision support tools for inventory-routing rescheduling problem. IJIEPR 2020; 31 (2) :203-215
URL: http://ijiepr.iust.ac.ir/article-1-1047-en.html
An optimization model based decision support tools for inventory-routing rescheduling problem
Parviz Fattahi 1, Mehdi Tanhatalab2 , Joerin Motavallian3 , Mehdi Karimi4
1- Alzahra University , p.fattahi@alzahra.ac.ir
2- Bu-Ali Sina University
3- RMIT University
4- Islamic Azad University, Science and Research Branch
Abstract:   (3810 Views)
The present work addresses inventory-routing rescheduling problem (IRRP) that is needed when some minor changes happen in the time of execution of pre-planned scheduling of an inventory-routing problem (IRP). Due to the complexity of the process of departing from one pre-planned scheduling IRP to a rescheduling IRP, here a decision-support tool is devised to help the decision-maker. This complexity comes from the issue that changes in an agreed schedule including the used capacity of the vehicle, total distance and other factors that need a re-agreements negotiation which directly relates to the agreed costs especially when a carrier contractor is responsible for the distribution of goods between customers. From one side he wants to stick to the pre-planned scheduling and from the other side, changes in predicted data of problem at the time of execution need a new optimized solution. The proposed approached applies mathematical modeling for optimizing the rescheduled problem and offers a sensitivity analysis to study the influence of the different adjustment of variables (carried load, distance, …). 
Keywords: inventory-routing rescheduling problem, decision support system, rescheduling
Full-Text [PDF 1029 kb]   (1487 Downloads)    
Type of Study: Research | Subject: Production Planning & Control
Received: 2020/04/11 | Accepted: 2020/04/18 | Published: 2020/06/27
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