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Robust Tabu Search Algorithm for Planning Rail-Truck Intermodal Freight Transport
Abstract
In this paper a new efficient tabu search algorithm for assigning freight to the intermodal transport connections was developed. There were also formulated properties of the problem that can be used to design robust heuristic algorithms based on the local search methods. The quality of solutions produced by the tabu search algorithm and by often recommended greedy approach were also compared.
This is the second half of a two part series devoted to the tabu search metastrategy for optimization problems. Part I introduced the fundamental ideas of tabu search as an approach for guiding other heuristics to overcome the limitations of local optimality, both in a deterministic and a probabilistic framework. Part I also reported successful applications from a wide range of settings, in which tabu search frequently made it possible to obtain higher quality solutions than previously obtained with competing strategies, generally with less computational effort. Part II, in this issue, examines refinements and more advanced aspects of tabu search. Following a brief review of notation, Part II introduces new dynamic strategies for managing tabu lists, allowing fuller exploitation of underlying evaluation functions. In turn, the elements of staged search and structured move sets are characterized, which bear on the issue of finiteness. Three ways of applying tabu search to the solution of integer programming problems are then described, providing connections also to certain nonlinear programming applications. Finally, the paper concludes with a brief survey of new applications of tabu search that have occurred since the developments reported in Part I. Together with additional comparisons with other methods on a wide body of problems, these include results of parallel processing implementations and the use of tabu search in settings ranging from telecommunications to neural networks.
INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.
Intermodal transport solutions, implying non-road freight transport on the long-haul, can contribute to the advance of more energy efficient transportation systems. This paper presents a model for analyzing the generalized transport cost of an intermodal transport solution. We find that the required long-haul distance required to make intermodal transport preferable increases when (1) handling costs at terminals increases, (2) total transport distance increases, (3) pre- and posthaulage costs increase, (4) distance dependent marginal generalized costs for rail increases, (5) the distance dependent marginal generalized costs for truck decreases and (6) reduced resting costs for truck drivers. The model results are discussed in light of transport of fresh aquaculture products from Norway to Continental Europe.
A logistics-based project is described which addresses the need for better intermodal transport, whilst balancing economic and environmental gains through the use of Internet technologies. Pipeline intermodal system to support control, expedition and scheduling (PISCES) provides an integrating platform for using these technologies in processing and sharing commercially sensitive data within transport chains (i.e. road, rail and barge). The paper demonstrates how information from an Internet-based system can be used to drive a scheduling tool to provide appropriate routes for the transport of goods, using a multimodal transport model.
This paper presents the fundamental principles underlying tabu search as a strategy for combinatorial optimization problems. Tabu search has achieved impressive practical successes in applications ranging from scheduling and computer channel balancing to cluster analysis and space planning, and more recently has demonstrated its value in treating classical problems such as the traveling salesman and graph coloring problems. Nevertheless, the approach is still in its infancy, and a good deal remains to be discovered about its most effective forms of implementation and about the range of problems for which it is best suited. This paper undertakes to present the major ideas and findings to date, and to indicate challenges for future research. Part I of this study indicates the basic principles, ranging from the short-term memory process at the core of the search to the intermediate and long term memory processes for intensifying and diversifying the search. Included are illustrative data structures for implementing the tabu conditions (and associated aspiration criteria) that underlie these processes. Part I concludes with a discussion of probabilistic tabu search and a summary of computational experience for a variety of applications. Part II of this study (to appear in a subsequent issue) examines more advanced considerations, applying the basic ideas to special settings and outlining a dynamic move structure to insure finiteness. Part II also describes tabu search methods for solving mixed integer programming problems and gives a brief summary of additional practical experience, including the use of tabu search to guide other types of processes, such as those of neural networks.
INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.
In this paper we propose a new neighborhood for the flexible job shop problem. A main idea of the proposed neighborhood is to execute a 'long shot' of an operation from the current operation's machine to another machine of the same type, and then to the make a small move by using a local optimization algorithm without changing operations-to-machines assignment. We call this method 'the golf neighborhood'. Computational experiments executed on the benchmark instances from the literature show the efficiency of this solution.
The recent development of Intelligent Transportation Systems offers the possibility of cooperative planning of multi-actor systems in a distributed framework, by enabling prompt exchange of information among actors. This paper proposes a modeling framework for cooperation in intermodal freight transport chains as multi-actor systems. In this framework, the problem of optimizing freight transportation is decomposed into a suitable set of sub-problems, each representing the operations of an actor which are connected using a negotiation scheme. A Discrete Event model is developed which optimizes the system on a rolling horizon basis to account for the dynamics of intermodal freight transport operations. This framework allows for an event driven short/medium term planning of intermodal freight transport chains. The proposed methodology is evaluated using a realistic case study, and the results are compared against the First-Come-First-Served strategy, highlighting the significance of cooperation in systems operating close to capacity.
In this paper we propose a new approach, recommended for solving certain class of multi-criteria scheduling problems, with the use of cloud exploration of the solution space supported by fine-grained parallel computing. The approach allow us to approximate Pareto front more accurately than other known algorithms in competitive time. To show and check advantageous properties of the proposed approach, the new solution algorithm, called VESA, was implemented for the case of bi-criteria flow shop scheduling problem and tested against a number of high-quality benchmarks known in the literature. Vector processing technologies are used to enhance the efficiency of solution search and acceptance rates for the extended simulated annealing metaheuristic. Results are compared using, among others, the independent Hyper-Volume Indicator (IH) measure. Computer test of VESA confirms excellent approximation of the Pareto front.
The paper deals with the parallel variant of the scheduling algorithm dedicated to the hybrid flow shop problem. The problem derives from practice of automated manufacturing lines, e.g. for printed packages. The overall goal is to design a new algorithm which merges the performance of the best known sequential approach with the efficient exploitation of parallel calculation environments. In order to fulfill the above aim, there are two methods proposed in this paper: the original fast method of parallel calculation of the criterion function and the local neighborhood parallel search method embedded in the tabu search approach. The theoretical analysis, as well as the original implementation, with the use of vector processing instructions SSE2 supported by suitable data organization, are presented below. Numerical properties of the proposed algorithm are empirically verified on the multi-core processor.
We propose a new method of sequential and par-allel speeding up of the process of solving a single machine scheduling problem with total tardiness cost function. This improvement is done on two levels: generating a neigh-borhood inside path relinking method (basing on new approach—blocks in solutions) and parallelization of gener-ating paths. The obtained results are compared to the bench-mark ones taken from the literature. It was possible to find new the best solutions for many benchmark instances by using the proposed method.
A fast and easily implementable approximation algorithm for the problem of finding a minimum makespan in a job shop is presented. The algorithm is based on a taboo search technique with a specific neighborhood definition which employs a critical path and blocks of operations notions. Computational experiments (up to 2,000 operations) show that the algorithm not only finds shorter makespans than the best approximation approaches but also runs in shorter time. It solves the well-known 10 \times 10 hard benchmark problem within 30 seconds on a personal computer.
The permutation flow shop sequencing problem with the objective of minimizing the sum of the job’s completion times, in literature
known as the F||C
sum
, has been considered. The parallel genetic algorithm based on the island model of migration has been presented. By computer
simulations on Taillard benchmarks [10] and the best known results from literature[9] we have obtained not only acceleration
of the computation’s time but also better quality and stability of the results.
Intermodal freight transport has developed into a significant sector of the transport industry in its own right. This development has been followed by an increase in intermodal freight transportation research. We contend that a new transportation research application field is emerging; and that, while still in a pre-paradigmatic phase, it is now time to move on to a more mature independent research field. An independent research field can be justified because intermodal transport is a complex system that has characteristics which distinguishes it from other transport systems. We have reviewed 92 publications in order to identify the characteristics of the intermodal research community and scientific knowledge base. This paper will discuss aspects of this research, assessing the status quo and seeking directions for the future. To conclude, we will propose an intermodal research agenda which can direct the intermodal research field towards a period of “normal science”.
This article describes a tabu search algorithm for the multi-depot vehicle routing problem with capacity and route length restrictions. The algorithm is tested on a set of 23 benchmark instances. It is shown to outperform existing heuristics.
In this paper we consider two routing problems: traveling salesman problem (TSP, fundamental problem of the combinatorial optimization) and the TSP with times of traveling, times of processing and due dates where the objective is to minimize the total weighted tardiness (TSPTWT). Since problems are NP-hard in the strong sense, we propose a metaheuristic algorithm to determine a good sub-optimal solution.We present an algorithm based on the idea of researching and analyzing local optima.TSP with times of traveling, times of processing and due dates, and with the total weighted tardiness cost function is identical with the single machine total weighted tardiness problem with sequence-dependent setup times. It was possible to find the new best known solutions for 81 of 120 benchmark instances of this scheduling problem using the method proposed here.
It is well known that in the standard traffic network equilibrium model with a single value of time (VOT) for all users, a so-called marginal-cost toll can drive a user equilibrium flow pattern to a system optimum. This result holds when either cost (money) or time units are used in expressing the objective function of the system optimum and the criterion for user equilibrium. This paper examines the multi-criteria or the cost-versus-time network equilibrium and system optimum problem in a network with a discrete set of VOTs for several user classes. Specifically, the following questions are investigated: Are the user-optimal flows dependent upon the unit (time or money) used in measuring the travel disutility in the presence of road pricing? Are there any uniform link tolls across all individuals (link tolls that are identical for all user classes) that can support a multi-class user equilibrium flow pattern as a system optimum when the system objective function is measured by either money or time units? What are the general properties of the valid toll set?
This paper presents a parallel tabu search algorithm for the container loading problem with a single container to be loaded. The emphasis is on the case of a weakly heterogeneous load. The distributed-parallel approach is based on the concept of multi-search threads according to Toulouse et al. [Issues in designing parallel and distributed search algorithms for discrete optimization problems, Publication CRT-96-36, Centre de recherche sur les transports, Universitéde Montréal, Canada, 1996] i.e., several search paths are investigated concurrently. The parallel searches are carried out by differently configured instances of a tabu search algorithm, which cooperate by the exchange of (best) solutions at the end of defined search phases. The parallel search processes are executed on a corresponding number of LAN workstations. The efficiency of the parallel tabu search algorithm is demonstrated by an extensive comparative test including well-known reference problems and loading procedures from other authors.
A simulation model of the flow of intermodal terminal units (ITUs) among and within inland intermodal terminals is presented. The intermodal terminals are interconnected by rail corridors. Each terminal serves a user catchment area via a road network. The terminal is modelled as a set of platforms, which are served by a number of gantry cranes and front lifters. The user of the simulation model defines the structure of the terminal and the train and truck arrival scenarios. The train arrivals are defined in a train timetable, while the patterns of truck arrivals for ITU delivery and pick-up can be either statistically modelled or given as a deterministic input. The simulator can be used to simulate both a single terminal and a rail network, that is, two or more interconnected terminals. During the simulation, various statistics are gathered to assess the performance of the terminal equipment, the ITU residence time, and the terminal throughput. The simulation software has been implemented as a discrete-event simulation model, using MODSIM III as development tool. The simulator tool has been developed as part of the Platform project, funded by the Directorate General VII of the European Community.
Intermodal transport reflects the combination of at least two modes of transport in a single transport chain, without a change of container for the goods, with most of the route traveled by rail, inland waterway or ocean-going vessel, and with the shortest possible initial and final journeys by road. Operational Research has focused mostly on transport problems of uni-modal transport modes. We argue that intermodal freight transportation research is emerging as a new transportation research application field, that it still is in a pre-paradigmatic phase, and that it needs a different type of models than those applicated to uni-modal transport. In this paper a review is given of the operational research models that are currently used in this emerging field and the modelling problems, which need to be addressed.
In this paper, we develop an extended guided tabu search (EGTS) and a new heuristic packing algorithm for the two-dimensional loading vehicle routing problem (2L-CVRP). The 2L-CVRP is a combination of two well-known NP-hard problems, the capacitated vehicle routing problem, and the two-dimensional bin packing problem. It is very difficult to get a good performance solution in practice for these problems. We propose a meta-heuristic methodology EGTS which incorporates theories of tabu search and extended guided local search (EGLS). It has been proved that tabu search is a very good approach for the CVRP, and the guiding mechanism of the EGLS can help tabu search to escape effectively from local optimum. Furthermore, we have modified a collection of packing heuristics by adding a new packing heuristic to solve the loading constraints in 2L-CVRP, in order to improve the cost function significantly. The effectiveness of the proposed algorithm is tested, and proven by extensive computational experiments on benchmark instances.
Pre- and end-haulage of intermodal container terminals involves the pickup or delivery of containers at customer locations. The attractiveness of intermodal transport can be increased by organizing the road segment in the intermodal transport chain more efficiently. In this paper the drayage of containers in the service area of an intermodal terminal is modelled as a full truckload pickup and delivery problem with time windows (FTPDPTW). A two-phase insertion heuristic is proposed to construct an initial solution. This solution is improved with a local search heuristic based on three neighbourhoods. Numerical experiments are described to demonstrate the mechanisms of the heuristics.
New parallel objective function determination methods for the job shop scheduling problem are proposed in this paper, considering makespan and the sum of jobs execution times criteria, however, the methods proposed can be applied also to another popular objective functions such as jobs tardiness or flow time. Parallel Random Access Machine (PRAM) model is applied for the theoretical analysis of algorithm efficiency. The methods need a fine-grained parallelization, therefore the approach proposed is especially devoted to parallel computing systems with fast shared memory (e.g. GPGPU, General-Purpose computing on Graphics Processing Units).
This paper describes a hybrid tabu search algorithm dedicated to a job shop problem with a no-wait constraint with a makespan criterion. The proposed here algorithm complexity is that the superior algorithm based on the tabu search technique selects parameters controlling the work of a certain constructional algorithm. This approach limits the checked solutions only to a group of solutions being able to be generated by the structural algorithm in question. It bears serious consequences both positive, for example it limits the research scope for a small fraction of relatively extremely well quality of acceptable solutions, and negative that is the lack of possibility of finding the optimal solution. In this paper numerical researches of the proposed algorithm are conducted as well as a comparative analysis with reference to the literature algorithms of the algorithm in question is made.