جستجوی مقالات مرتبط با کلیدواژه "hub location" در نشریات گروه "مدیریت"

Hazardous materials which are materials due to their chemical and physical properties impose significant risk to the safety of people and the environment. It's more complex routing transport of such material than normal materials. The Combination of the two subjects as the problem of locating and routing, it has created unified system to locating- routing problems. These problems determined optimal number and location of facilities at the same time and also set the optimal number of vehicles and their routes. The purpose of this study was design a network for the transportation of hazardous materials and includes supply levels, distribution (hub) and customers. Hence, it presented a mathematical model in order to minimizing costs and risk simultaneously. Hazardous materials sent from supplier to the hubs and deliveries to customers from there via routing by road transportation. It should be mentioned that in proposal model the hubs been locating In order to validate the model, prepared code GAMS In software and for the exact solution, sample problems with various dimensions were produced in the form of smart and random. For this purpose, was written an algorithm design in Matlab software. According to the problem was NP-Hard, presented a hybrid algorithm based on simulated annealing and genetic algorithms to solve large-scale. At the end of research the proposed algorithm were compared with the results of exact solution.

This paper presents the hierarchical cycle hub location problem. This new problem is an extension of the cycle hub location problem (CHLP). It is a three-layered hub network problem where the top level consists of a cycle network connecting the so-called central hubs and the second and third level are unions of star networks connecting the intermediate hubs to central hubs and the demand centers to intermediate and central hubs, respectively. The problem is to decide on the locations of a predetermined number of intermediate and central hubs and the connections in order to minimize the total routing cost in the resulting network. We also propose two mixed integer linear programming formulations for the problem. The behavior of the proposed models, in terms of solution time, is evaluated on the basis of an extensive computational study on Turkish pastal network dataset. The results achieved by CPLEX and Xpress solvers, based on the proposed MILP formulation, are compared to each other. We have also reduced the time to solve the problem by changing the parameters of the solver

Hub location problem (HLP) is one of the strategic planning problems in logistics with numerous applications in passenger/cargo transportation, postal services, telecommunications, etc. This paper addresses the competitive single allocation HLP where the market is assumed to be a duopoly. Two firms (decision makers) sequentially decide on the configuration of their hub networks trying to maximize their own market shares and the customers choose one firm based on the service level (cost, distance, and etc.) provided by these firms. Mathematical formulations are provided for the problems of the first and second firms (the leader and the follower, respectively) and a tabu search (TS) based solution algorithm is proposed for solving the leader's and the follower's problems. Standard data sets, which exist in the literature of HLP, have been used to validate the solution methods and mathematical models. Computational experiments show that considering the competition in deciding on the location of hubs can positively affect the captured market share from the international shipping markets.

In order to manage the expenditures in a road transportation network in which the transport demands between cities are less than a truckload capacity, one needs to determine the location of hubs at first, and then collect the cargo from the cities in some routes which are assigned to the appropriate hubs. In this paper, a special case of hub location-routing issue was considered that is suitable for the particular conditions of Iran as cities are located in the sparse and distant places. A mixed integer mathematical programming model was proposed. As the model is NP-hard in nature, a two-phase hybrid method including genetic algorithms and simulated annealing was designed to solve the model. The results of the comparison between the model and the outputs demonstrated the accuracy and speed of the proposed solution method. Finally, a real case including all 31 capital cities of Iran provinces was solved to illustrate the appropriate performance of the solution method.

This paper aims to model and resolve single allocation multi-product hierarchical hub location problem with considering of uncertainty and quality of service. The designed hierarchical hub network has three levels that the top one consists of fully connected central hub nodes and second and third levels are star network of non-central hub nodes with central hub nodes and demand centers to hub nodes (central and non-central), respectively. In the proposed model, objective functions minimizes the sum of transportation and delay costs beside the cost of activating the inactive airline routs, and thereby optimal decision is made on location of hubs, allocation of non-hub nodes to hub nodes and the type of transportation vehicle. For evaluation of the proposed model a collected dataset of Iran is used. Sensitivity analysis of model’s behavior with parameters’ change is done and resulted in management implications.

Parcel delivery is a complex logistic service, as it serves many small or medium-sized customers who may send or receive parcels. Modeling such delivery system needs to integrate two different research areas of hub location and vehicle routing. As it totally depends on the network and the linkage of the nodes, in this paper, some door-to-door service providers are taken into account to provide suitable information for modeling parcel deliveries of sparse and wide countries. Since the proposed mixed-integer programming model is NP-hard, a new multi-steps solution method based on a simulated annealing algorithm and local search is presented. The results of the proposed model and the solution method are evaluated based on some small test problems. The performance of the solution method is illustrated by solving a real case with all capital cities of 31 provinces in Iran.