Abstract
In this paper, we propose a new model for the multi-objective multiple allocation hub network design and routing problem which contains determining the location of hubs, the design of hub network, and the routing of commodities between source-destination pairs in the given network. The selected hubs are not assumed to be fully connected, and each node and arc in the network has capacity constraints. The multiple objectives of the problem are the minimization of total fixed and transportation costs and the minimization of the maximum travel time required for routing. We propose a mathematical formulation for the multi-objective problem and present a meta-heuristic solution based on a well-known multi-objective evolutionary algorithm. Using the proposed formulation, we are able to find the optimal solution for small networks of five nodes and seven nodes. To evaluate the performance of our heuristic approach on real data, the computational experiments are conducted on Turkish postal system data set. The results demonstrate that our heuristic approach can find feasible solutions to the problem in reasonable execution time, which is less than 10 min.
Highlights
There are plenty of applications that need transfer of people, commodities and data between source-destination pair of nodes, such as, air transportation services, public postal services, cargo delivery systems, and telecommunication systems
To contribute to fill this gap, we propose a mathematical model for the MOCMAHLP with objectives of (1) minimizing transportation cost and fixed costs and (2) minimizing the maximum travel time required for routing the commodities between all node pairs
MATHEMATICAL MODEL we present a new model for the Multiobjective Capacitated Multiple Allocation Hub Location Problem (MOCMAHLP)
Summary
There are plenty of applications that need transfer of people, commodities and data between source-destination pair of nodes, such as, air transportation services, public postal services, cargo delivery systems, and telecommunication systems. We concentrate on multi-objective, capacitated, multiple allocation HLP; and in our mathematical formulation of the given problem, we consider determining the location of hubs, spoke-to-hub and hub-to-hub allocations, and routing of commodities between each pair of nodes. In a recent study [20], Mirzaei and Bashiri present a model for multi-objective multiple allocation hub location problem In their model, the hub network is assumed to be fully interconnected and no experimental result is given in the corresponding paper. Mirzaei and Bashiri [20] consider a multi-objective approach for HLP to minimize the total cost and to minimize the maximum traveling time between nodes in the network.
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