Vahid Babaveisi, Farnaz Barzinpour, Ebrahim Teimoury,
Volume 31, Issue 1 (IJIEPR 2020)
Abstract
In this paper, an inventory-routing problem for a network of appliance repair service is discussed including several repair depots and customers. The customer in this network makes a demand to have his/her faulty appliance repaired. Then, the repairman is assigned to the demand based on the skill needed for repairing of appliance differing for each one. The assigned repairman picks up the faulty appliance from the customer place using the vehicle for transferring faulty appliances to repair depot. The vehicle for picking up and delivering the appliances has a maximum capacity. Additionally, the repair depot needs spare parts to repair the faulty appliances that is supplied either by the supplier or lateral transshipment from the other depots. The capacitated vehicle inventory-routing problem with simultaneous pickup and delivery is NP-hard which needs special optimization procedure. Regarding the skill of repairman, it becomes more complex. Many solution approaches have been provided so far which have their pros and cons to deal with. In this study, an augmented angle-based sweep method is developed to cluster nodes for solving the problem. Finally, the heuristic is used in the main body of genetic algorithm with special representation.
Tahere Hashemi, Ebrahim Teimoury, Farnaz Barzinpour,
Volume 31, Issue 3 (IJIEPR 2020)
Abstract
Retailers selling fresh products often encounter unsold inventory remains at the end of each period. The leftover product has a lower perceived quality than the new product. Therefore, retailers try to influence consumers’ preferences through price differentiation that leads to an internal competition based on product age and prices. This paper addresses the pricing and inventory control problem for fresh products to capture the influence of this competition on the supply chain members’ decisions and profits. A new coordination model based on a return policy with the revenue and cost-sharing contract is developed to improve the profits of independent supply chain members. The supply chain consists of one supplier and one retailer, where consumers are sensitive to the product’s retail price and freshness degree. Firstly, the retailer’s optimal decisions are derived in a decentralized decision-making structure. Then a centralized approach is used to optimize the supply chain decisions from the whole supply chain viewpoint. Eventually, a new coordination contract is designed to convince the members to participate in the coordination model. Numerical examples are carried out to compare the performance of different decision-making approaches. Our findings indicate that the proposed contract can coordinate the supply chain effectively. Furthermore, the coordinated decision-making model is more profitable and beneficial for the whole supply chain compared to the decentralized one. The results also demonstrate that when consumers are more sensitive to freshness, the simultaneous sale of multiple-aged products at different prices is more profitable.
