Wout Dullaert

A memetic algorithm for bi-objective integrated forward/reverse logistics network design

Logistics network design is a major strategic issue due to its impact on the efficiency and responsiveness of the supply chain. This paper proposes a model for integrated logistics network design to avoid the sub-optimality caused by a separate, sequential design of forward and reverse logistics networks. First, a bi-objective mixed integer programming formulation is developed to minimize the total costs and maximize the responsiveness of a logistics network. To find the set of non-dominated solutions, an efficient multi-objective memetic algorithm is developed. The proposed solution algorithm uses a new dynamic search strategy by employing three different local searches. To assess the quality of the novel solution approach, the quality of its Pareto-optimal solutions is compared to those generated by an existing powerful multi-objective genetic algorithm from the recent literature and to exact solutions obtained by a commercial solver.

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 heuristics performance. Experimental results on Solomons and Gehring and Homberger benchmarks demonstrate that our algorithm outperforms previous approaches and is able to improve 184 best-known solutions out of 356 instances.

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 simultaneously to exploit economies of scale. This paper provides estimates of synergy values, both in a constructed benchmark case and in a number of real-world cases. Findings - It turns out that synergy values of 30% are achievable. Furthermore, intuition is developed on how the synergy values depend on characteristics of the distribution problem under consideration. Practical implications - the developed intuition on the nature of synergy values can help practitioners to find suitable combinations of distribution systems, since synergy values can quickly be assessed based on the characteristics of the distribution problem, without solving large and difficult Vehicle Routing Problems. Originality/value - this paper addresses a major impediment to horizontal cooperation: estimating operational savings upfront.

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 initial solutions are generated by means of a savings-based heuristic that combines diversification strategies with learning mechanisms. In Phase 2, an attempt is made to reduce the number of routes in the initial solution with a new local search procedure. In Phase 3, the solution from Phase 2 is further improved by a set of four local search operators that are embedded in a deterministic annealing framework to guide the improvement process. Some new implementation strategies are also suggested for efficient time window feasibility checks. Extensive computational experiments on the 168 benchmark instances have shown that the suggested method outperforms the previously published results and found 167 best-known solutions. Experimental results are also given for the new problem variant.

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 customers.

An optimization approach for communal home meal delivery service: A case study

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.

Logistic Efficiency Through Horizontal Cooperation : The Case of Flemish Road Transportation Companies

This paper describes a practical application of Data Envelopment Analysis (DEA) to the Flemish road transportation sector.The efficiency of 82 road transportation companies responding to a large-scale survey focused on horizontal cooperation is evaluated, based on two inputs and two outputs.Various DEA models are used to identify differences between subgroups of respondents.The results demonstrate that, in general, Flemish road transportation companies operate at unacceptably low efficiency levels.Given the findings that the median company is operating on too small a scale one apparent remedy would be a dramatic increase in market concentration through mergers and acquisitions

Market Efficiency Within Dry Bulk Markets in the Short Run: A Multi-Agent System Dynamics Nash Equilibrium

In this paper, we assess the Efficient Market Hypothesis (EMH) in relation to dry bulk shipping in the short run. The aim is to explain why freight rates in the different ship segments are highly correlated. By building a system dynamics model, which is well-suited to modelling complex and stochastic processes with limited data availability, we attempt to track the arbitrage process in which the different ship types (Handy, Panamax and Capesize) literally seek to transport each others’ cargoes (substitution) when this is beneficial. Also, within one ship segment, we govern the arbitrage opportunities arising from regional differences in freight rates. Although the EMH is ever more contested in the maritime literature, holistic and analytical proof is provided that efficiency is maintained through the intrinsic arbitrage free and evolutionary behaviour in the system towards the Nash equilibrium.

An upper bound on the cycle time of a stochastic marked graph using incomplete information on the transition firing time distributions

Stochastic marked graphs, a special class of stochastic timed Petri nets, are used for modelling and analyzing decision-free dynamic systems with uncertainties in timing. The model allows evaluating the performance of such systems under a cyclic process. Given the probabilistic characteristics of the transition times, the cycle time of the system can be determined from the initial marking. In this contribution, we compute an upper bound on the cycle time of a stochastic marked graph in case the probabilistic characteristics of the transition times are not fully specified.

Designing a decision support model for the LNG market

Abstract As the Liquefied Natural Gas (LNG) market is supply-driven and subject to long-term contracts, both liquefaction companies and shipowners need to make strategic decisions on fleet chartering requirements. These planning decisions become ever more difficult in light of the transformations permeating the LNG market, propelling into a more competitive market with more flexible trades and expanding spot markets. The overcapacity of LNG ships during 2008–2009 triggered by massive overcontracting is a good case in point where the use of decision support models would have been beneficial, especially considering the fortunes and risks at stake. In this paper we present an LNG shipping model that effectively supports decision-making in practice. To demonstrate the value added of the model, we study the implications of LNG project delays and increased decommissioning of ships with respect to market balance and fleet requirements.