A Programmed Solution for Approximating an Optimum Retail Location

Huff, David L.

doi:10.2307/3145346

Cited by 217 publications

(119 citation statements)

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“… A facility may be chosen for other purposes by the customer (Carling & Håkansson, 2013). A more actual model for explaining the customers' behaviour could be developed by applying The Gravity Rule (Reilly, 1931) or the later (Huff, 1964(Huff, , 1966. According to The Gravity Rule, the probability that a customer chooses a facility depends on the attractiveness and decreasing function of distance to a facility.…”

Section: Fig 1 the Graphical Representation Of Nodes In A Transportmentioning

confidence: 99%

Many to many hub and spoke location routing problem based on the gravity rule

Khosravi¹,

Jokar²

2018

10.5267/j.uscm

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This paper examines the spoke and hub location decisions in a routing problem. To minimize the total cost, the study analyzes on how to locate the spokes, hubs and the allocation of spoke nodes to hub nodes, the routing among the nodes and the number of vehicles assigned to each hub thoroughly. As there might be no facility assigned to some points, unsatisfied demands must be distributed to other nodes with available facilities. Furthermore, the realized demand is determined by considering the perceived utility of each path, using The Gravity rule. For this purpose, the proposed nonlinear model is transformed into a linear programming model, where some tightening rules and preprocessing procedures are applied, and also the sequential and integrated approaches are developed to solve the problem. In the sequential method, spokes are allocated, and hubs are selected based on the location of the spokes, after which the routing in the local tour is determined. Meanwhile, in the integrated approach, the aggregated model is solved. A heuristic is presented to address the integrated model. Numerical experiments are run on both approaches, to compare both, and obtain insights from the model.

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Section: Fig 1 the Graphical Representation Of Nodes In A Transportmentioning

confidence: 99%

Many to many hub and spoke location routing problem based on the gravity rule

Khosravi¹,

Jokar²

2018

10.5267/j.uscm

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“…According to the literature customer demand can be inelastic or elastic, and elastic demand can depend on price, service, price and service, or price and distance . On the other hand, deterministic utility function (introduced by Hotelling 1929) and random utility function (introduced by Huff 1964Huff , 1966 are the most common functions in the CSCND, SC competition and competitive location literature. In deterministic utility model, the customers visit the facility with the highest utility, whereas in random utility they visit each facility by a certain probability that is directly related to the attractiveness level of the facility and inversely related to the attractiveness level of all the existing facilities.…”

Section: Literature Reviewmentioning

confidence: 99%

Decentralized supply chain network design: monopoly, duopoly and oligopoly competitions under uncertainty

2017

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This paper presents the competitive supply chain network design problem in which n decentralized supply chains simultaneously enter the market with no existing rival chain, shape their networks and set wholesale and retail prices in competitive mode. The customer demand is elastic and price dependent, customer utility function is based on the Hoteling model and the chains produce identical or highly substitutable products. We construct a solution algorithm based on bi-level programming and possibility theory. In the proposed bi-level model, the inner part sets the prices based on simultaneous extra-and Stackleberg intra-chains competitions, and the outer part shapes the networks in cooperative competitions. Finally, we use a real-word study to discuss the effect of the different structures of the competitors on the equilibrium solution. Moreover, sensitivity analyses are conducted and managerial insights are offered.

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“…Facility size, or square footage, is a surrogate for facility attractiveness. Huff [62,63] depicted equiprobability lines. A customer located on such a line between two facilities patronizes the two facilities with equal probability.…”

Section: Introductionmentioning

confidence: 99%

“…Many models estimate market share based on the gravity rule (Huff [62,63]). Nakanishi and Cooper [72] suggested the multiplicative competitive interaction (MCI) approach for estimating attractiveness level of facilities.…”

Section: Introductionmentioning

confidence: 99%

“…An alternative probabilistic approach to estimating market share, based on the gravity model (Reilly [78]), was introduced by Huff [62,63] and is used by marketers. According to the gravity model, two cities attract retail trade from an intermediate town in direct proportion to the populations of the two cities and in inverse proportion to the square of the distances from them to the intermediate town.…”

Section: Introductionmentioning

confidence: 99%

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Modeling Competitive Facility Location Problems: New Approaches and Results

Berman¹,

Drezner²,

Drezner³

et al. 2009

Decision Technologies and Applications

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The gravity model as applied to competitive facility location is described in this tutorial. The gravity model is used mainly by marketers to estimate the market share attracted by competing retail facilities. A demand area consists of potential customers who spend their discretionary buying power at competing retail facilities. We discuss the gravity model and issues related to the determination of the parameters of the models. The basic model is to find the best locations for new facilities that would attract the maximum buying power from customers in the area. Extensions to this basic model include modeling uncertainty about future market conditions, minimizing the probability that the attracted market share falls short of a certain target, demand generated by intercepting a flow of customers, market expansion and lost demand, and allocation of a given budget among one's facilities to improve their attractiveness. We describe special tools that are utilized in the solution procedures. These are the generalized Weiszfeld procedure, the big triangle small triangle global optimization approach, and the tangent line approximation.

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A Programmed Solution for Approximating an Optimum Retail Location

Cited by 217 publications

References 0 publications

Many to many hub and spoke location routing problem based on the gravity rule

Many to many hub and spoke location routing problem based on the gravity rule

Decentralized supply chain network design: monopoly, duopoly and oligopoly competitions under uncertainty

Modeling Competitive Facility Location Problems: New Approaches and Results

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