Transportation industry is a fairly large industry in today's globalized world, and has significant effect too. Each and every big or small industry is bound to use the transportation facilities or logistics. The main problems in this logistics operation are optimizing the cost, time; distance traveled, back orders and surpluses. In most of the studies, one or two of the aspects mentioned above has been taken into consideration and solved accordingly. Again in a lot of studies, it was assumed that the demand structure, inventory structure, structure of cluster formation and structure of route formation are of deterministic nature. This study is trying to find out a combined comprehensive methodology to optimize all the aspects of loss of a logistical system, keeping in consideration that most of the structures mentioned above have human decision making component and thus, obviously of fuzzy nature.
Logistics (which is basically the science of movement of materials, intermediaries and final products from the producer to customer) costs constitute a major portion of the total costs in a supply chain and hence efforts on minimizing costs in this area are a challenging job. Transportation plays an important role in logistics and hence is critical sub-function.
[...] There are some other possible methods like Simulated Annealing and Tabu Search, which may come handy to develop the process further. The approach to solve the multi product multi objective multi modal vehicle routing problem will follow simultaneously the process of route optimization and the cluster optimization. These two processes will continue in parallel with mutual development and will contain a part of human decision making procedure which is obviously fuzzy. The demand structure and the inventory structure will also surely be of fuzzy nature in the proposed research methodology. This study will start with the mathematical modeling approach. [...]
[...] A model and methodologies for the location problem with logistical components. Computers & Operations Research 1173–1193. Zhou, G., Min, H., & Gen, M. (2002). The balanced allocation of customers to multiple distribution centers in the supply chain network: A genetic algorithm approach. Computers & Industrial Engineering 252–261. Jayaraman, V., & Pirkul, H. (2001). Planning and coordination of production and distribution facilities for multiple commodities. European Journal of Operational Research 394–408. Park, Y. (2001). A hybrid genetic algorithm for the vehicle scheduling problem with due times and time deadlines. [...]
[...] Possible Outcomes from the Study From this study, it is expected to get a developed and more capable heuristic approach for minimizing the time, cost, distance and inventory for a multi-product and multi-modal distribution system. This heuristic approach is expected to work for very large scale distribution problems, which will be extremely beneficial for the global players of transportation. This study is expected to deliver a combined approach to minimize all possible aspects of logistical loss from the point of view of the supplier/manufacturer. [...]
[...] First, the initial solution was obtained by using Solomon's insertion heuristic procedure, and was improved through a combination of λ-interchanges and 2-opt exchanges to find a good solution for the problem Taillard et al (1997) introduced a Tabu search heuristic for the VRP with soft time windows. The original problem was converted into the vehicle routing problem with hard time windows by adding large penalty values, and then an exchange procedure was used to swap sequences of consecutive customers between two routes. [...]
[...] Bison, ed., A Look Back from the Year 2000, 28th Annual Meeting of the Canadian Transportation Research Forum, 30-40. Assad, A.A. (1980), "Models for rail transportation", Transportation Research A 14, 205-220. Taillard, E. (1993), "Parallel iterative search methods for vehicle routing problems", Networlc~ 23, 661-673. Zalatan, P. (1993), "Economic cycles, structural change and the transportation sector", in: B.G. Bison, ed., A look Back from the Year 2000, 28th Annual Meeting of the Canadian Transportation Research Forum, 111-121. Button, K.J. (1993), Transport Economics, Edward Elgar. [...]
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