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Showing 4 results for Yaser
Ms. Maryam Akbari-Jafarabadi, Prof. Reza Tavakkoli-Moghaddam, Mr. Mehdi Mahmoodjanloo, Mr. Yaser Rahimi,
Volume 6, Issue 2 (9-2015)
Abstract
In general, any system may be at risk in a case of losing the critical facilities by natural disasters or terrorist attacks. This paper focuses on identifying the critical facilities and planning to reduce the effect of this event. A three-level model is suggested in the form of a defender-attacker-defender. It is assumed that the facilities are hierarchical and capable of nesting. Also, the attacker budget for the interdiction and defender budget for fortification is limited. At the first level, a defender locates facilities in order to enhance the system capability with the lowest possible cost and full covering customer demand before any interdiction. The worst-case scenario losses are modeled in the second-level. At the third level, a defender is responsible for satisfying the demand of all customers while minimizing the total transportation and outsourcing costs. We use two different approaches to solve this model. In the first approach, the third level of the presented model is coded in Gams software, its second level is solved by an explicit enumeration method, and the first level is solved by tabu search (TS). In the second approach the first level is solved by the bat algorithm (BA). Finally, the conclusion is provided.
Mr. Yaser Rouzpeykar , Dr Roya Soltani, Dr Mohammad Ali Afashr Kazemi,
Volume 11, Issue 1 (9-2020)
Abstract
The hub location and revenue management problem are two research topics in the field of network design and transportation. The hub location model designs the structure of the transportation network, while the revenue management model allocates network capacity to different customer categories according to their price sensitivity. Revenue management determines which products to sell to which customers and at what price. On the other hand, due to the limited number of aircraft seats, the revenue management problem has been widely used in the aviation industry. In this study, a robust optimization model is developed for the hub location and revenue management problem. For this purpose, a real-world case study with a central hub and six airports is presented and solved using CPLEX solver in GAMS software. Finally, a sensitivity analysis was performed on the key parameters of the problem, and their effect on the objective functions of the problem was investigated. Results show that the proposed model achieved the feasible solution in reasonable time for real case problem by exact method.
Mr Yaser Khosravian, Prof Ali Shahandeh Nookabadi, Prof Ghasem Moslehi,
Volume 15, Issue 1 (7-2024)
Abstract
Traditional maximal p-hub covering problems focus on scenarios where network flow is constrained by resource limitations. However, many existing models rely on static parameters, overlooking the inherent randomness present in real-world logistics. This oversight can result in suboptimal network designs that are vulnerable to congestion and rising costs as demand varies. To address this issue, we propose a novel mathematical model for the capacitated single allocation maximal p-hub covering problem that takes into account stochastic variations in origin-destination flows. Although solving this model poses computational challenges, we utilize a Lagrangian relaxation algorithm to enhance efficiency. Computational experiments using the CAB dataset highlight the effectiveness of our approach in achieving optimal solutions while reducing computation time. This framework offers valuable insights for designing robust hub-and-spoke networks in the face of demand uncertainty.
Roghayeh Yaser, Hadi Nasseri,
Volume 15, Issue 2 (12-2024)
Abstract
Supplier selection is one of the main discussions in the Supply Chain. The issue of assigning purchase orders to suppliers that act differently in terms of quality, cast, services, etc. criteria is one of the significant concerns of purchase managers in the supply chain. To adopt an optimal decision in this regard is related to a multi-objective problem that the objectives are contradicting each other and have different importance and priority depending on the location. In practice, the existence of kind of ambiguity in explaining the information related to the problem constraints and complicated. In this regard, the emergence of Fuzzy set theory as a tool to describe such conditions besides presenting question model realistically can help to solve such problems well. Despite the importance of the model with the mentioned structure, unfortunately, few original works have been done in this field. As a result, in this paper, in addition to presenting a new multi-objective Fuzzy model being modelled based on assigning purchase order to suppliers in a supply chain a solution method is introduced based on using Fuzzy linear programming. To clarify solution process modelling and description, a case study is included related to selecting flour supplier for providing industrial bread of Khoshkar factory. The proposed model includes four objective functions:
- Aggregate costs of minimizing type,
- Services of maximizing type (such as packing, being faithful to promise, factory heath, discount, correct transportation, good relationships, honestly, etc.),
- Flour useful survival of maximizing type (regarding monthly flour buying by the factory),
- The purchased flour quality of maximizing type (concerning product type).
Especially in the solution process, a method is determined based on setting weight for each of the objectives concerning the major factory stockholders.
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