Metaheuristic Approaches for Solving Truck and Trailer Routing Problems with Stochastic Demands: A Case Study in Dairy Industry

Mathematical Problems in Engineering, Oct 2015

Manufacturers and service providers often encounter stochastic demand scenarios. Researchers have, thus far, considered the deterministic truck and trailer routing problem (TTRP) that cannot address ubiquitous demand uncertainties and/or other complexities. The purpose of this study is to model the TTRP with stochastic demand (TTRPSD) constraints to bring the TTRP model closer to a reality. The model is solved in a reasonable timeframe using data from a large dairy service by administering the multipoint simulated annealing (M-SA), memetic algorithm (MA), and tabu search (TS). A sizeable number of customers whose demands follow the Poisson probability distribution are considered to model and solve the problem. To make the solutions relevant, first, 21 special TTRPSD benchmark instances are modified for this case and then these benchmarks are used in order to increase the validity and efficiency of the aforementioned algorithms and to show the consistency of the results. Also, the solutions have been tested using sensitivity analysis to understand the effects of the parameters and to make a comparison between the best results obtained by three algorithms and sensitivity analysis. Since the differences between the results are insignificant, the algorithms are found to be appropriate and relevant for solving real-world TTRPSD problem.

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Metaheuristic Approaches for Solving Truck and Trailer Routing Problems with Stochastic Demands: A Case Study in Dairy Industry

Metaheuristic Approaches for Solving Truck and Trailer Routing Problems with Stochastic Demands: A Case Study in Dairy Industry Seyedmehdi Mirmohammadsadeghi and Shamsuddin Ahmed Manufacturing System Integration, Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia Received 18 July 2014; Revised 13 November 2014; Accepted 18 December 2014 Academic Editor: Yi-Chung Hu Copyright © 2015 Seyedmehdi Mirmohammadsadeghi and Shamsuddin Ahmed. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Manufacturers and service providers often encounter stochastic demand scenarios. Researchers have, thus far, considered the deterministic truck and trailer routing problem (TTRP) that cannot address ubiquitous demand uncertainties and/or other complexities. The purpose of this study is to model the TTRP with stochastic demand (TTRPSD) constraints to bring the TTRP model closer to a reality. The model is solved in a reasonable timeframe using data from a large dairy service by administering the multipoint simulated annealing (M-SA), memetic algorithm (MA), and tabu search (TS). A sizeable number of customers whose demands follow the Poisson probability distribution are considered to model and solve the problem. To make the solutions relevant, first, 21 special TTRPSD benchmark instances are modified for this case and then these benchmarks are used in order to increase the validity and efficiency of the aforementioned algorithms and to show the consistency of the results. Also, the solutions have been tested using sensitivity analysis to understand the effects of the parameters and to make a comparison between the best results obtained by three algorithms and sensitivity analysis. Since the differences between the results are insignificant, the algorithms are found to be appropriate and relevant for solving real-world TTRPSD problem. 1. Introduction These days, complex customer demands are required to be satisfied by many companies. Therefore, a large number of companies are trying to achieve a high level of reliability, flexibility, and agility for different demands. As a result, supply chain management (SCM) has become a thought-provoking subject for various companies, seeking for a way out of efficiently improving their customer satisfaction. In a way, according to the position and role, supply chain is categorized into three classes; the outbound, intracompany, and inbound supply chain. As the network of supplies begins at the inbound supply chain, the role of this group is transporting the semifinished products or the raw materials to the site of manufacturing. The main concern of the intracompany supply chain, as the intermediary part, is with the flow of material in the site of manufacturing. Finally, the outbound supply chain is concerned with the delivery of final products to the customers [1]. The inventory allocation and transportation are strongly considered in the outbound supply chain for minimizing the cost and satisfying the customers’ demands. One significant part of the supply chain management is providing the services or/and goods from a supply point to different destinations, which are geographically distributed with significant implications of economics. Aside from the cost of purchasing the goods, on the average and compared to the other relative activities, a higher percentage of the costs of logistics are absorbed by transportation. Therefore, efficiency improvement through the maximum usage of the necessities of transportation and decreasing the costs of transportation along with the improvement of services for customers are the frequent and significant decision analysis problems [2]. Customers, warehouses, manufacturers, and suppliers are the main elements of a supply chain (SC), carrying the goods from the upstream to the downstream links of the chain. In a supply chain, there are four main business functions to be performed: purchasing, manufacturing, inventory, and distribution. The function of distribution includes two activities: the shipment of finished products from the companies to the locations of demand, and transportation of parts or raw materials from the suppliers to the companies [3]. In order to manage a supply chain, a large number of business processes need to be carried out and many decisions are required to be made. Particular design versions of these general supply systems and inventory planning problems have been studied for a long time. It is pretty obvious that these main supply chain problems are greatly related. As the time goes by, more companies are awakened about their supply chain performance and how important it is that they improve this performance. They also have become aware of the competitive advantage of distribution operations, i (...truncated)


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Seyedmehdi Mirmohammadsadeghi, Shamsuddin Ahmed. Metaheuristic Approaches for Solving Truck and Trailer Routing Problems with Stochastic Demands: A Case Study in Dairy Industry, Mathematical Problems in Engineering, 2015, 2015, DOI: 10.1155/2015/494019