Title: Developing a multi-method simulation model of a green closed-loop supply chain and determining pricing and advertising policy against a competitor

Authors: Samira Parsaiyan; Maghsoud Amiri; Parham Azimi; Mohammad Taghi Taqhavi Fard

Addresses: Department of Industrial Management, Allameh Tabataba'i University, Dehkadeh Square, Olympic Blvd., Tehran, Postal Code: 1489684511, Iran ' Department of Industrial Management, Allameh Tabataba'i University, Dehkadeh Square, Olympic Blvd., Tehran, Postal Code: 1489684511, Iran ' Department of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University – Nokhbegan Blvd., Qazvin, Postal Code: 1519534199, Iran ' Department of Industrial Management, Allameh Tabataba'i University, Dehkadeh Square, Olympic Blvd., Tehran, Postal Code: 1489684511 Iran

Abstract: The environmental impact of supply chains has motivated many studies in this area. This research proposes a novel multi-method simulation approach which combines agent-based and discrete event modelling approaches to model a green closed-loop supply chain and optimise it through an optimisation via simulation technique. A closed-loop supply chain is developed under the demand uncertainty to minimise total cost and total greenhouse gases (GHG) emissions and maximise management preference of the supply chain in the presence of a competitor. Taguchi design of experiments method is used to generate scenarios, then total cost and total GHG emissions are recorded through simulating the scenarios. Management preference is determined based on decision makers' opinion. Scenarios are ranked against three attributes with the proposed panel-group TOPSIS method. Inventory replenishment parameters, pricing and advertising policies, and transportation type are determined via solving the model. An automotive industry case is provided to demonstrate the model's capabilities.

Keywords: green closed-loop supply chain; agent-based modelling; multi-method simulation; pricing policy; advertising policy; TOPSIS.

DOI: 10.1504/IJBPSCM.2019.105690

International Journal of Business Performance and Supply Chain Modelling, 2019 Vol.10 No.4, pp.283 - 322

Received: 13 Jun 2018
Accepted: 17 Apr 2019
Published online: 09 Mar 2020 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article