Fariborz Jolai; Reza Tavakolli Moghaddam; Jafar Razmi; Pedaram Sahba
Abstract
In this paper, a supplier-retailer transportation system is investigated as a two-echelon environment. There is a single location in each echelon; the unique supplier at the first echelon has to replenish the retailer's warehouse at the second echelon. By the way, the shortage situation should be avoided. ...
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In this paper, a supplier-retailer transportation system is investigated as a two-echelon environment. There is a single location in each echelon; the unique supplier at the first echelon has to replenish the retailer's warehouse at the second echelon. By the way, the shortage situation should be avoided. For this situation, a model is provided based on the traditional EOQ model. The inventory costs, ordering costs, transportation cost, etc. are considered in this model. Multistage shipment during each ordering period with a specific number of vehicles is allowed in the proposed model. The model's decisions involved in managing the system include design decision (i.e., optimized number of required vehicles), as well as operation decision (i.e., optimized order quantity and number of trips and transportation stages). A solution algorithm is proposed for the proposed model and implemented with C#.Net which is available and applicable on the website, namely www.PedramSahba.com. A numerical example and sensitivity analysis are presented for exposing the model and algorithm capability and then verifying and validating the model.
Reza Tavakoli Moghadam; Fariborz Jolai; Somayyeh Ghandi Beygi
Abstract
The parallel machine scheduling problem is an important and difficult problem to be considered in the real-world situations. Traditionally, this problem consists of the scheduling of a set of independent jobs on parallel machines with the aim of minimizing the maximum job completion. In today's manufacturing ...
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The parallel machine scheduling problem is an important and difficult problem to be considered in the real-world situations. Traditionally, this problem consists of the scheduling of a set of independent jobs on parallel machines with the aim of minimizing the maximum job completion. In today's manufacturing systems, in which both early and tardy finishing of job processing are undesired, the objectives related to earliness and tardiness penalties have become increasingly popular. In this paper, two major goals are considered as follows: (1) total weighted earliness; (2) total weighted tardiness. Due to the complexity of such a hard problem, a new multi-objective meta-heuristic method, i.e. multi-objective scatter search (MOSS), is proposed to obtain the locally Pareto-optimal frontier where the simultaneous minimization of the above-mentioned objectives is desired. In order to validate the performance of the proposed MOSS method, in terms of solution quality and diversity level, various test problems are considered and the reliability of this method, based on different comparison metrics, is compared with the Elite Tabu Search (ETS) devised in this paper. The computational results show the high capability of the proposed MOSS method.
