This paper shows how the subtour elimination constraints developed by Miller, Tucker and Zemlin for the traveling salesman problem can be improved and extended to various types of vehicle routing problems (A)

Improvements and extensions to the miller-tucker-zemlin subtour elimination constraints

The process of distributing perishable goods considering quality is an important competitive and complicated task. In this paper, a novel mixed-integer linear programming (MILP) model is proposed to consider a location routing problem (LRP) for multiple perishable products with multi-trip vehicles having multiple trips, intermediate depots, and soft time windows. To cope with the solution complexity of the problem, an efficient biography based optimization algorithm (BBO) is designed. The algorithm is enhanced by tuning its parameters using Taguchi design method. In the first phase of the computational results, the proposed mathematical model is validated using CPLEX solver of GAMS in small-sized problems as an exact method. At the second phase, the performance of the proposed algorithm is evaluated compared to CPLEX, and it is demonstrated that it has an appropriate performance to generate high-quality and near-optimum solutions with the average gap of 0.839% for 3600 seconds of runtime limitation. Finally, a sensitivity analysis is performed on the demand parameter to study the behavior of the objective function in the real world condition.

An Efficient Biography-Based Optimization Algorithm to Solve the Location Routing Problem With Intermediate Depots for Multiple Perishable Products

Bangladesh is blessed with various agro-based natural resources like Date sap, extracted from date trees. As this date sap is found in rural areas in large quantities annually but a very small fraction is converted into some value-added delicious foods at a domestic level while a large portion is left underutilized due to negligence, improper collection, and preservation system from the industry level. The processed delicious foods have conspicuous demand in the national market due to their nutritious value and the growth of the national economy. Despite its economic importance, very little researches have been conducted in this field for its industrial processing. So, this research implies to improve this straggled sector providing much attention for collecting raw sap from source and processing into value-added products from industrial level cost-effectively. The key objectives of this paper are to determine optimal facility location for processing date sap and set vehicle routes that can pick up date sap from source to processing plant simultaneously curtailing operational transportation costs. Initially, a Mixed Integer Linear Programming (MILP) model is introduced to determine optimal facility location. Besides, the Large Neighborhood Search (LNS) algorithm has been used to find the optimal set of vehicle routes. This paper outlines a summary of final results that Jessore (A south-western city in Bangladesh) is an optimal plant location and 10 vehicles are necessary for covering 15 areas which ultimately optimize the total supply time, respecting constraints concerning routing, timing, capacity, and supply as well transportation costs.

http://www.journal-aprie.com/article_132553_829f99e0372752c492c1f77f4b400e96.pdf

Md. Aqib Aman

Papers

Determining optimal production plant location and vehicle route in upstream supply chain network for date sap processing industry