Comparing descent heuristics and metaheuristics for the vehicle routing problem

Breedam, Alex Van

doi:10.1016/s0305-0548(99)00101-x

Cited by 99 publications

(29 citation statements)

References 34 publications

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“…For example, Osman [24] combined TS and SA concepts for the solution search during routing improvement. Van Breedam [25] used three types of routing improvement methods, and then added SA mechanisms for improvements. Tan et al [26] combined TS, SA, and GA to solve the VRP with time window.…”

Section: Approaches For Vrpmentioning

confidence: 99%

Minimizing the Carbon Footprint for the Time-Dependent Heterogeneous-Fleet Vehicle Routing Problem with Alternative Paths

et al. 2014

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Torespondto the reduction of greenhouse gas emissions and global warming, this paper investigates the minimal-carbon-footprint time-dependent heterogeneous-fleet vehicle routing problem with alternative paths (MTHVRPP). This finds a route with the smallestcarbon footprint, instead of the shortestroute distance, which is the conventional approach, to serve a number of customers with a heterogeneous fleet of vehicles in cases wherethere may not be only one path between each pair of customers, and the vehicle speed differs at different times of the day. Inheriting from the NP-hardness of the vehicle routing problem, the MTHVRPP is also NP-hard. This paper further proposes a genetic algorithm (GA) to solve this problem. The solution representedbyour GA determines the customer serving ordering of each vehicle type. Then, the capacity check is used to classify multiple routes of each vehicle type, and the path selection determines the detailed paths of each route. Additionally, this paper improves the energy consumption model used for calculating the carbon footprint amount more precisely. Compared with the results without alternative paths, our experimental results show that the alternative path in this experimenthas a significant impact on the experimental results in terms of carbon footprint.

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Section: Approaches For Vrpmentioning

confidence: 99%

Minimizing the Carbon Footprint for the Time-Dependent Heterogeneous-Fleet Vehicle Routing Problem with Alternative Paths

et al. 2014

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“…In order to narrow the search space and make the process more intelligent, a criterion, called the range delimiter, has been proposed to prevent the selection of too many bad moves (Breedam 2001). The concept of delimiter value is similar to the generation of an initial solution described in the previous Section.…”

Section: Delimiter Valuementioning

confidence: 99%

Optimal Coordination Strategy for an Integrated Multimodal Transit Feeder Network Design Considering Multiple Objectives

Almasi

Sadollah

et al. 2018

Sustainability

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Public transportation can have an efficient role ingainingtraveler satisfaction while decreasing operation costs through establishing an integrated public transit system. The main objective of this research is to propose an integrated multimodal transit model to design the best combination of both railway and feeder bus mode transit systems, while minimizing total cost. In this paper, we have proposed a strategy for designing transit networks that provide multimodal services at each stop, and for consecutively assigning optimum demand to the different feeder modes. Optimum transit networks have been achieved using single and multi-objective approaches via metaheuristic optimization algorithms, such as simulated annealing, genetic algorithms, and the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The used input data and study area were based on the real transit network of Petaling Jaya, located in Kuala Lumpur, Malaysia. Numerical results of the presented model, containing the statistical results, the optimum demand ratio, optimal solution, convergence rate, and comparisons among best solutions have been discussed in detail.

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“…Application of meta-heuristics in location and vehicle-routing is abundant (Golden and Skiscim 1986;Tuzun and Burke 1999;Prins et al 2007;Bräysy et al 2009;Prins et al 2009). It has been reported that Tabu Search and Simulated Annealing are appropriate meta-heuristics for solving NPhard combinatorial optimisation problems (Breedam 2001) of location-routing. However plenty of scope is still there to judge the efficacy of other meta-heuristics in solving locationrouting problems.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated low-carbon distribution system for the demand side of a product distribution supply chain: a DoE-guided MOPSO optimiser-based solution approach

Validi

Bhattacharya

Byrne

2013

International Journal of Production Research

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This article contributes to location-routing literature on three inter-linked aspects viz., formulation of a novel integrated low-carbon/green location-routing model for the demand side of a Supply Chain (SC) with a single product and multiple consumers, i.e., Drop-off Points (DoPs), a novel and robust solution approach through a Design of Experiment (DoE)-guided Multiple-Objective Particle Swarm Optimisation (MOPSO) optimiser and exhaustive analysis of the location-routing solutions (i.e., prioritisation, ranking and scenario analysis). The total costs, CO 2 emission and the traversed distances of the vehicles during transportation are optimised. The optimisation model for the strategic decision-making is formulated by effectively integrating the 0-1 mixed-integer programming with a green constraint based on Analytic Hierarchy Process (AHP). Due to the computationally NP-hard characteristic of the model a systematic and technically robust DoE-guided solution approach is designed using a commercial solver -modeFRONTIER ® .DoE guides the solution through the MOPSO optimiser in order to eliminate the un-realistic set of feasible and optimal solution sets. A popular multi-attribute decision-making approach, TOPSIS, evaluates the solutions found from the Pareto optimal solution space of the solver. Finally decision-makers' preferences are analysed for monitoring the changes in the controlling parameters with respect to the changes in the decisions. A scenario analysis of the location-routing events by considering alternative possible outcomes is also conducted. It is found that the implemented methodology successfully routes the vehicles with optimal costs and low-carbon emission thus contributing to greening the environment on the demand side of a SC network.

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Comparing descent heuristics and metaheuristics for the vehicle routing problem

Cited by 99 publications

References 34 publications

Minimizing the Carbon Footprint for the Time-Dependent Heterogeneous-Fleet Vehicle Routing Problem with Alternative Paths

Minimizing the Carbon Footprint for the Time-Dependent Heterogeneous-Fleet Vehicle Routing Problem with Alternative Paths

Optimal Coordination Strategy for an Integrated Multimodal Transit Feeder Network Design Considering Multiple Objectives

Integrated low-carbon distribution system for the demand side of a product distribution supply chain: a DoE-guided MOPSO optimiser-based solution approach

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