جستجوی مقالات مرتبط با کلیدواژه "demand uncertainty" در نشریات گروه "علوم پایه"

The vehicle routing problem has attracted much attention in the recent decade. Considering the real-world constraints, many extensions have been developed. This paper develops a new model for the green vehicle routing problem with simultaneous pickup and delivery under demand uncertainty. Due to the problem's complexity, the standard solvers are only able to solve small-scale instances. To solve the large-scale problems, a two-stage algorithm based on the modified AVNS is proposed. Extensive computational experiments are conducted using modified versions of Solomon’s benchmark instances to show the performance of the algorithm. The results affirm that the two-stage algorithm is capable of generating optimal solutions for small-size instances and the planned routes generated for large-size instances were significantly more robust against the increase of uncertainty parameters.

A Location-Arc Routing Problem (LARP) is a practical problem, while a few mathematical programming models have been considered for this problem. In this paper, a mixed non-linear programming model is presented for a multi-period LARP with the time windows under demand uncertainty. The time windows modeling in the arc routing problem is rarely. To the best our knowledge, it is the first time that the robust LARP model is verified and an optimal solution is presented for it. For this purpose, the CPLEX solver is used for solving the treasury location problems of a bank as a case study. These problems are node-based with close nods and can be transformed into arc-based. Therefore, the method LRP and LARP models can be used to solve these problems. The comparing results of the LRP and LARP models prove that the LARP has a better performance regarding timing and optimal solution. Furthermore, comparing the results of deterministic and robust LARP models for this case study shows the validity of the robust optimization approach.

The system of distribution of goods and services, along with other economic developments aroundthe world, is rapidly evolving. In the world of distribution of goods, the main focus is on makingdistribution operations more effective. Due to the fact that the cross-dock has the advantage ofremoving intermediaries and reducing the space required for the warehouse, it is worth considering.Among the methods of cross-docking, the post-distribution method is important in terms of uncer-tainty. Due to the importance of the issue of the post-distribution method in cross-dock, this paperaddresses the uncertainty of demand in cross-docking. For this purpose, a linear programming modelhas been developed for post-distribution cross-dock, and then solved an example by the use of themeta-heuristic whale algorithm. After that, uncertainty enters the model and the robust counterpartof the model present based on the robust optimization approach with using interval and polyhedralcollective inductive uncertainty set. The results shows the model could control the demand uncer-tainty in distance zero until 20 percent and the model does not let the changing of demand effortsconsiderably on the scheduling of the cross-docking.