0000000000179530

AUTHOR

Wout Dullaert

0000-0002-9416-211x

A well-scalable metaheuristic for the fleet size and mix vehicle routing problem with time windows

This paper presents an efficient and well-scalable metaheuristic for fleet size and mix vehicle routing with time windows. The suggested solution method combines the strengths of well-known threshold accepting and guided local search metaheuristics to guide a set of four local search heuristics. The computational tests were done using the benchmarks of [Liu, F.-H., & Shen, S.-Y. (1999). The fleet size and mix vehicle routing problem with time windows. Journal of the Operational Research Society, 50(7), 721-732] and 600 new benchmark problems suggested in this paper. The results indicate that the suggested method is competitive and scales almost linearly up to instances with 1000 custome…

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The potential of optimization in communal routing problems: case studies from Finland

Abstract: In many European countries, municipalities offer their inhabitants a wide variety of social services. In this paper we will focus on efficiently scheduling home care, transportation of the elderly, and home meal delivery. These so-called municipal or communal routing problems can be modeled as different variants of the vehicle routing problem, a well-known optimization problem from the literature. We present a focused literature review and report on case studies using Finnish data. The computational results show that there is a significant potential for cost savings for all applications considered.

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Using a TSP heuristic for routing order pickers in warehouses

In this paper, we deal with the sequencing and routing problem of order pickers in conventional multi-parallel-aisle warehouse systems. For this NP-hard Steiner travelling salesman problem (TSP), exact algorithms only exist for warehouses with at most three cross aisles, while for other warehouse types literature provides a selection of dedicated construction heuristics. We evaluate to what extent reformulating and solving the problem as a classical TSP leads to performance improvements compared to existing dedicated heuristics. We report average savings in route distance of up to 47% when using the LKH (Lin-Kernighan-Helsgaun) TSP heuristic. Additionally, we examine if combining problem-sp…

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An Effective Multirestart Deterministic Annealing Metaheuristic for the Fleet Size and Mix Vehicle-Routing Problem with Time Windows

This paper presents a new deterministic annealing metaheuristic for the fleet size and mix vehicle-routing problem with time windows. The objective is to service, at minimal total cost, a set of customers within their time windows by a heterogeneous capacitated vehicle fleet. First, we motivate and define the problem. We then give a mathematical formulation of the most studied variant in the literature in the form of a mixed-integer linear program. We also suggest an industrially relevant, alternative definition that leads to a linear mixed-integer formulation. The suggested metaheuristic solution method solves both problem variants and comprises three phases. In Phase 1, high-quality init…

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A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windows

In this paper, we present an effective memetic algorithm for the vehicle routing problem with time windows (VRPTW). The paper builds upon an existing edge assembly crossover (EAX) developed for the capacitated VRP. The adjustments of the EAX operator and the introduction of a novel penalty function to eliminate violations of the time window constraint as well as the capacity constraint from offspring solutions generated by the EAX operator have proven essential to the heuristic's performance. Experimental results on Solomon's and Gehring and Homberger benchmarks demonstrate that our algorithm outperforms previous approaches and is able to improve 184 best-known solutions out of 356 instance…

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A Simple Metaheuristic for the FleetSize and Mix Problem with TimeWindows

This paper presents a powerful new single-parameter metaheuristic to solve the Fleet Size and Mix Vehicle Routing Problem with Time Windows. The key idea of the new metaheuristic is to perform a random number of random-sized jumps in random order through four well-known local search operators. Computational testing on the 600 large-scale benchmarks of Bräysy et al. (Expert Syst Appl 36(4):8460–8475, 2009) show that the new metaheuristic outperforms previous best approaches, finding 533 new best-known solutions. Despite the significant number of random components, it is demonstrated that the variance of the results is rather low. Moreover, the suggested metaheuristic is shown to scale almost…

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Joint Route Planning under Varying Market Conditions

Purpose - To provide empirical evidence on the level of savings that can be attained by joint route planning and how these savings depend on specific market characteristics.Design/methodology/approach - Joint route planning is a measure that companies can take to decrease the costs of their distribution activities. Essentially, this can either be achieved through horizontal cooperation or through outsourcing distribution to a Logistics Service Provider. The synergy value is defined as the difference between distribution costs in the original situation where all entities perform their orders individually, and the costs of a system where all orders are collected and route schemes are set up s…

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Joint route planning under varying market conditions

PurposeTo provide empirical evidence on the level of savings that can be attained by joint route planning and how these savings depend on specific market characteristics.Design/methodology/approachJoint route planning is a measure that companies can take to decrease the costs of their distribution activities. Essentially, this can either be achieved through horizontal cooperation or through outsourcing distribution to a logistics service provider. The synergy value is defined as the difference between distribution costs in the original situation where all entities perform their orders individually, and the costs of a system where all orders are collected and route schemes are set up simulta…

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Communal Transportation: Challenges for Largescale Routing Heuristics

In this report we review the central transportation logistics problems arising in the communal sector, using information gathered from several large communes in Finland and previous literature. Most of the communal transportation problems can be modelled as different variants of the vehicle routing problem. The basic features of the problems are described, modelled and analyzed, and the relevant previous research on the topics is reviewed. In addition, some possible new solution strategies are suggested.

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An optimization approach for communal home meal delivery service

Abstract: This paper is the first to discuss the communal home meal delivery problem. The problem can be modelled as a multiple travelling salesman problem with time windows, that is closely related to the well-studied vehicle routing problem with time windows. Experimental results are reported for a real-life case study from Central Finland over several alternative scenarios using the SPIDER commercial solver. The comparison with current practice reveals that a significant savings potential can be obtained using off-the-shelf optimization tools. As such, the potential for supporting real-life communal routing problems can be considered to be important for VRP practitioners.

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A multi-parametric evolution strategies algorithm for vehicle routing problems

Vehicle routing problems are at the heart of most decision support systems for real-life distribution problems. In vehicle routing problem a set of routes must be determined at lowest total cost for a number of resources (i.e. fleet of vehicles) located at one or several points (e.g. depots, warehouses) in order to efficiently service a number of demand or supply points. In this paper an efficient evolution strategies algorithm is developed for both capacitated vehicle routing problem and for vehicle routing problem with time window constraints. The algorithm is based on a new multi-parametric mutation procedure that is applied within the 1 + 1 evolution strategies algorithm. Computational …

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