A novel facility location problem for taxi hailing platforms

2020 ◽  
Vol 120 (3) ◽  
pp. 526-546 ◽  
Author(s):  
Hong Ma ◽  
Ni Shen ◽  
Jing Zhu ◽  
Mingrong Deng
Keyword(s):  
Facility Location ◽  
Location Problem ◽  
Facility Location Problem ◽  
Time Constraints ◽  
Data Sets ◽  
Trajectory Data ◽  
Content Type ◽  
Regional Demand ◽  
New Variant ◽  
Vehicle Trajectory

Purpose Motivated by a problem in the context of DiDi Travel, the biggest taxi hailing platform in China, the purpose of this paper is to propose a novel facility location problem, specifically, the single source capacitated facility location problem with regional demand and time constraints, to help improve overall transportation efficiency and cost. Design/methodology/approach This study develops a mathematical programming model, considering regional demand and time constraints. A novel two-stage neighborhood search heuristic algorithm is proposed and applied to solve instances based on data sets published by DiDi Travel. Findings The results of this study show that the model is adequate since new characteristics of demand can be deduced from large vehicle trajectory data sets. The proposed algorithm is effective and efficient on small and medium as well as large instances. The research also solves and presents a real instance in the urban area of Chengdu, China, with up to 30 facilities and demand deduced from 16m taxi trajectory data records covering around 16,000 drivers. Research limitations/implications This study examines an offline and single-period case of the problem. It does not consider multi-period or online cases with uncertainties, where decision makers need to dynamically remove out-of-service stations and add other stations to the selected group. Originality/value Prior studies have been quite limited. They have not yet considered demand in the form of vehicle trajectory data in facility location problems. This study takes into account new characteristics of demand, regional and time constrained, and proposes a new variant and its solution approach.

A revised weighted fuzzy c-means and Nelder-Mead algorithm for probabilistic demand and customer positions

2021 ◽  
pp. 1-11
Author(s):  
Engin Bayturk ◽  
Sakir Esnaf ◽  
Tarik Kucukdeniz
Keyword(s):  
Facility Location ◽  
Location Problem ◽  
Facility Location Problem ◽  
Service Level ◽  
Data Sets ◽  
Location Selection ◽  
Fuzzy C Means ◽  
Np Hard Problem ◽  
Fuzzy C Means Algorithm ◽  
Customer Demands

Facility location selection is a vital decision for companies that affects both cost and delivery time over the years. However, determination of the facility location is a NP-hard problem. A hybrid algorithm that combines revised weighted fuzzy c-means with Nelder Mead (RWFCM-NM) performs well when compared with well-known algorithms for the facility location problem (FLP) with deterministic customer demands and positions. The motivation of the study is both analyzing performance of the RWFCM-NM algorithm with probabilistic customer demands and positions and proposing a new approach for this problem. This paper develops two new algorithms for FLP when customer demands and positions are probabilistic. The proposed algorithms are a probabilistic fuzzy c-means algorithm and Nelder-Mead (Probabilistic FCM-NM), a probabilistic revised weighted fuzzy c-means algorithm and Nelder Mead (Probabilistic RWFCM-NM) for the un-capacitated planar multi-facility location problem when customer positions and customer demands are probabilistic with predetermined service level. Proposed algorithms performances were tested with 13 data sets and comparisons were made with four well known algorithms. According to the experimental results, probabilistic RWFCM-NM algorithm demonstrates superiority on compared algorithms in terms of total transportation costs.

Solving Uncapacitated Facility Location Problem Using Heuristic Algorithms

2019 ◽  
Vol 8 (2) ◽  
pp. 18-50 ◽  
Author(s):  
Soumen Atta ◽  
Priya Ranjan Sinha Mahapatra ◽  
Anirban Mukhopadhyay
Keyword(s):  
Facility Location ◽  
Heuristic Algorithm ◽  
Optimization Problem ◽  
Location Problem ◽  
Heuristic Algorithms ◽  
Randomized Algorithm ◽  
Facility Location Problem ◽  
Deterministic Algorithm ◽  
Data Sets ◽  
Uncapacitated Facility Location Problem

A well-known combinatorial optimization problem, known as the uncapacitated facility location problem (UFLP) is considered in this article. A deterministic heuristic algorithm and a randomized heuristic algorithm are presented to solve UFLP. Though the proposed deterministic heuristic algorithm is very simple, it produces good solution for each instance of UFLP considered in this article. The main purpose of this article is to process all the data sets of UFLP available in the literature using a single algorithm. The proposed two algorithms are applied on these test instances of UFLP to determine their effectiveness. Here, the solution obtained from the proposed randomized algorithm is at least as good as the solution produced by the proposed deterministic algorithm. Hence, the proposed deterministic algorithm gives upper bound on the solution produced by the randomized algorithm. Although the proposed deterministic algorithm gives optimal results for most of the instances of UFLP, the randomized algorithm achieves optimal results for all the instances of UFLP considered in this article including those for which the deterministic algorithm fails to achieve the optimal solutions.

scholarly journals Dispersing Obnoxious Facilities on a Graph

Algorithmica ◽  
2021 ◽  
Author(s):  
Alexander Grigoriev ◽  
Tim A. Hartmann ◽  
Stefan Lendl ◽  
Gerhard J. Woeginger
Keyword(s):  
Facility Location ◽  
Location Problem ◽  
Unit Length ◽  
Facility Location Problem ◽  
Np Hard ◽  
Obnoxious Facilities ◽  
Rational Parameter ◽  
Polynomially Solvable

AbstractWe study a continuous facility location problem on a graph where all edges have unit length and where the facilities may also be positioned in the interior of the edges. The goal is to position as many facilities as possible subject to the condition that any two facilities have at least distance $$\delta$$ δ from each other. We investigate the complexity of this problem in terms of the rational parameter $$\delta$$ δ . The problem is polynomially solvable, if the numerator of $$\delta$$ δ is 1 or 2, while all other cases turn out to be NP-hard.

Fuzzy facility location problem with preference of candidate sites

2007 ◽  
Vol 158 (17) ◽  
pp. 1922-1930 ◽  
Author(s):  
Hiroaki Ishii ◽  
Yung Lung Lee ◽  
Kuang Yih Yeh
Keyword(s):  
Facility Location ◽  
Location Problem ◽  
Facility Location Problem
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