Robust optimization for the hierarchical mixed capacitated general routing problem applied to winter road maintenance

Ahabchane, Chahid; Trépanier, Martin

doi:10.1016/j.cie.2021.107396

Cited by 8 publications

(4 citation statements)

References 40 publications

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“…The authors propose to tackle the problem using tabu search. Ahabchane et al [1] address a hierarchical salt spreading model, where priorities are included in the objective function. The latter consists of the total routing costs and the sum product of weights given according to the priorities and the times they are serviced.…”

Section: Literature Reviewmentioning

confidence: 99%

A rolling horizon framework for the time‐dependent multi‐visit dynamic safe street snow plowing problem

Fröhlich,

Gansterer,

Doerner

2023

Networks

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As a major real‐world problem, snow plowing has been studied extensively. However, most studies focus on deterministic settings with little urgency yet enough time to plan. In contrast, we assume a severe snowstorm with little known data and little time to plan. We introduce a novel time‐dependent multi‐visit dynamic safe street snow plowing problem and formulate it on a rolling‐horizon‐basis. To solve this problem, we develop an adaptive large neighborhood search as the underlying method and validate its efficacy on team orienteering arc routing problem benchmark instances. We create real‐world‐based instances for the city of Vienna and examine the effect of (i) different snowstorm movements, (ii) having perfect information, and (iii) different information‐updating intervals and look‐aheads for the rolling horizon method. Our findings show that different snowstorm movements have no significant effect on the choice of rolling horizon settings. They also indicate that (i) larger updating intervals are beneficial, if prediction errors are low, and (ii) larger look‐aheads are better suited for larger updating intervals and vice versa. However, we observe that less look‐ahead is needed when prediction errors are low.

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Section: Literature Reviewmentioning

confidence: 99%

A rolling horizon framework for the time‐dependent multi‐visit dynamic safe street snow plowing problem

Fröhlich,

Gansterer,

Doerner

2023

Networks

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“…Being a relatively young field of operational research, during the last two decades, robust optimization has become largely popular, as a modeling substratum for the protection against variable uncertainties in mathematical optimization [9][10][11][12][13][14][15][16][17][18][19][20].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Variables n own kr , n in kr and x kr are design variables and z h od s is control variable. Following ζ s from (25) and objective function (14)…”

Section: Robust Optimization Modelmentioning

confidence: 99%

Distributionally Robust Model and Metaheuristic Frame for Liner Ships Fleet Deployment

2022

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The container shipping industry market is very dynamic and demanding, economically, politically, legally, and financially. Considering the high cost of core assets, ever rising operating costs, and the volatility of demand and supply of cargo space, the result is an industry under enormous pressure to remain profitable and competitive. To maximize profits while maintaining service levels and ensuring the smooth flow of cargo, it is essential to make strategic decisions in a timely and optimal manner. Fleet deployment selection, which includes the profile of vessel hire, as well as their capacity and port rotation, is one of the most important strategic and tactical decisions container shipping operators must make. Bearing in mind that maritime business is inherently stochastic and uncertain, the key aims of this paper are to address the problem of fleet deployment under uncertain operating conditions, and to provide an integrated and optimized tool in the form of a mathematical model, metaheuristic algorithm, and computer program. Furthermore, this paper will show that the properties of the provided solutions exceed those offered in the literature so far. Such a solution will provide the shipping operator with a decision tool to best deploy its fleet in a way that responds more closely to real life situations and to meet the maximum demand for cargo space with minimal expense. The final goal is to minimize the operating costs while managing cargo flows and reducing the risks of unfulfilled customer demands.

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“…The study of Korteweg et al [11] also presented a method of improving the HCCP by considering the lexicographic criterion which minimizes priority class costs. Ahabchane et al [12] addressed the issue of road salt spreading during the winter season by presenting a variant of the Slack Induction by String Removals (SISRs) metaheuristic. In this study, an optimization method for the road priority hierarchy was developed by formulating the mixed capacitated general routing problem with demand variation due to traffic or weather conditions.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Snowplow Routes for Real-World Conditions

Abdullah

Seo

et al. 2022

Sustainability

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During the winter season, snowplowing has a significant effect on road users as it is critical to winter road maintenance and operations. The main goal of this study is to generate optimal routes for snowplowing trucks for efficient road maintenance. In addition to the conventional problem of reducing travel time and distance, this study also incorporates actual operational constraints, such as minimum maintenance standards and driver safety, to improve the overall efficiency of operations. To achieve the objectives, we first implemented the Chinese Postman Problem (CPP) to create Euler circuits from the initial routes and then identified the shortest paths by applying Dijkstra’s algorithm. Then, the Tabu search algorithm was chosen as a metaheuristic algorithm for the optimization process that finds near-optimal solutions by considering operational constraints for snowplow routes. Unsafe turning conditions and minimum maintenance standards were taken into account in the objective function defined for the optimization process. In simulations, the route obtained by our approach was compared to one with the application of CPP only in terms of travel distance, time, turning conditions, and road maintenance priority.

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Robust optimization for the hierarchical mixed capacitated general routing problem applied to winter road maintenance

Cited by 8 publications

References 40 publications

A rolling horizon framework for the time‐dependent multi‐visit dynamic safe street snow plowing problem

A rolling horizon framework for the time‐dependent multi‐visit dynamic safe street snow plowing problem

Distributionally Robust Model and Metaheuristic Frame for Liner Ships Fleet Deployment

Optimization of Snowplow Routes for Real-World Conditions

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