An efficient heuristic algorithm for the alternative-fuel station location problem

Tran, Trung Hieu; Nagy, Gábor; Nguyen, Thu Ba T.; Wassan, Niaz A.

doi:10.1016/j.ejor.2017.10.012

Cited by 34 publications

(14 citation statements)

References 46 publications

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“…To minimize the total cost to locate electric vehicle charging stations in road networks, Gagarin and Corcoran [51] suggest a novel approach that searches for the dominating set of locations among the candidate locations whose distance is below a certain threshold from a given driver. Using a parallel computing strategy, Tran et al [52] propose an efficient heuristic algorithm for location of AF refueling stations based on the solution of a sequence of subproblems. e major differences between the proposed model and the existing studies that are directly relevant to ours are summarized in Table 2.…”

Section: Main Distinctions Of Our Research Workmentioning

confidence: 99%

An Alternative Fuel Refueling Station Location Model considering Detour Traffic Flows on a Highway Road System

Hwang

Kweon

Ventura

2020

Journal of Advanced Transportation

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With the development of alternative fuel (AF) vehicle technologies, studies on finding the potential location of AF refueling stations in transportation networks have received considerable attention. Due to the strong limited driving range, AF vehicles for long-distance intercity trips may require multiple refueling stops at different locations on the way to their destination, which makes the AF refueling station location problem more challenging. In this paper, we consider that AF vehicles requiring multiple refueling stops at different locations during their long-distance intercity trips are capable of making detours from their preplanned paths and selecting return paths that may be different from original paths for their round trips whenever AF refueling stations are not available along the preplanned paths. These options mostly need to be considered when an AF refueling infrastructure is not fully developed on a highway system. To this end, we first propose an algorithm to generate alternative paths that may provide the multiple AF refueling stops between all origin/destination (OD) vertices. Then, a new mixed-integer programming model is proposed to locate AF refueling stations within a preselected set of candidate sites on a directed transportation network by maximizing the coverage of traffic flows along multiple paths. We first test our mathematical model with the proposed algorithm on a classical 25-vertex network with 25 candidate sites through various scenarios that consider a different number of paths for each OD pair, deviation factors, and limited driving ranges of vehicles. Then, we apply our proposed model to locate liquefied natural gas refueling stations in the state of Pennsylvania considering the construction budget. Our results show that the number of alternative paths and deviation distance available significantly affect the coverage of traffic flows at the stations as well as computational time.

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Section: Main Distinctions Of Our Research Workmentioning

confidence: 99%

An Alternative Fuel Refueling Station Location Model considering Detour Traffic Flows on a Highway Road System

Hwang

Kweon

Ventura

2020

Journal of Advanced Transportation

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“…The authors presented a study of a real case and implemented an ILS algorithm for the routing and mathematical techniques for the loading of vehicles. On the other hand, Tran et al [22] implemented a heuristic algorithm for location of alternative-fuel stations. Hosseinabadi et al [23] developed a method called TIME_GELS that uses the gravitational emulation local search algorithm (GELS) for solving the multiobjective flexible dynamic job-shop scheduling problem.…”

Section: Literature Reviewmentioning

confidence: 99%

A Heuristic Algorithm for the Routing and Scheduling Problem with Time Windows: A Case Study of the Automotive Industry in Mexico

et al. 2019

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This paper investigates a real-world distribution problem arising in the vehicle production industry, particularly in a logistics company, in which cars and vans must be loaded on auto-carriers and then delivered to dealerships. A solution to the problem involves the loading and optimal routing, without violating the capacity and time window constraints for each auto-carrier. A two-phase heuristic algorithm was implemented to solve the problem. In the first phase the heuristic builds a route with an optimal insertion procedure, and in the second phase the determination of a feasible loading. The experimental results show that the purposed algorithm can be used to tackle the transportation problem in terms of minimizing total traveling distance, loading/unloading operations and transportation costs, facilitating a decision-making process for the logistics company.

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“…In the literature review, there are four formulations for the FRLM without station failures [for example, Kuby and Lim (2005), Capar and Kuby (2012), MirHassani and Ebrazi (2013) and Capar et al (2013)]. The model developed by Capar et al (2013) is known as the most efficient formulation for the FRLM so far, since the number of variables (i.e., binary and continuous) and the number of constraints in this model are smaller than others (Tran et al 2017a). Based on the formulation of Capar et al (2013), we develop an MINLP model for the FRLM with station failures in the next section.…”

Section: Formulation Of the Standard Frlmmentioning

confidence: 99%

“…A specialized metaheuristic algorithm based on Simulated Annealing is developed to solve the large-size problem in a reasonable computation time. Tran et al (2017a) develop an efficient heuristic algorithm for the FRLM. This algorithm is built based on solving the sequence of sub-problems that are restricted on a set of promising station candidates, and fixing a number of the best promising station locations.…”

Section: Introductionmentioning

confidence: 99%

Alternative-fuel station network design under impact of station failures

Tran

Nguyen

2018

Ann Oper Res

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In this paper, we have formulated a mixed-integer non-linear programming model for alternative-fuel station location problem in which each station can fail with a site-specific probability. The model aims to maximise the total expected traffic volume that can be refuelled by the unreliable alternative-fuel stations. Based on the linearisation techniques, i.e., probability chains and piecewise-linear functions, we linearise the non-linearity of compound probability terms in the non-linear model to solve this problem efficiently. An efficient Tabu search algorithm is also developed to solve the large-size instances. In addition, we extend the model to deal with reliable multi-period alternative-fuel station network design. Computational experiments, carried out on the well-known benchmark instances where the probability of station failures is uniformly generated, show that the proposed models and algorithm can obtain the optimal solutions within a reasonable computation time. Compared to a standard station location model that disregards the potential for station failures, our model designs more reliable alternative-fuel station network under risk of station failures. A sensitivity analysis of failure probabilities in the station network design is investigated to demonstrate the robustness of our model and study how variability in the probability of station failure affects solution robustness.

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An efficient heuristic algorithm for the alternative-fuel station location problem

Cited by 34 publications

References 46 publications

An Alternative Fuel Refueling Station Location Model considering Detour Traffic Flows on a Highway Road System

An Alternative Fuel Refueling Station Location Model considering Detour Traffic Flows on a Highway Road System

A Heuristic Algorithm for the Routing and Scheduling Problem with Time Windows: A Case Study of the Automotive Industry in Mexico

Alternative-fuel station network design under impact of station failures

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