Time Windows (VRPTW) and shows that implementing algorithms for solving various instances of VRPs... more Time Windows (VRPTW) and shows that implementing algorithms for solving various instances of VRPs can significantly reduce transportation costs that occur during the delivery process. Two metaheuristic algorithms were developed for solving VRPTW: Simulated Annealing and Iterated Local Search. Both algorithms generate initial feasible solution using constructive heuristics and use operators and various strategies for an iterative improvement. The algorithms were tested on Solomon's benchmark problems and real world vehicle routing problems with time windows. In total, 44 real world problems were optimized in the case study using described algorithms. Obtained results showed that the same distribution task can be accomplished with savings up to 40% in the total travelled distance and that manually constructed routes are very ineffective.
In solving the real-world transport tasks, it is not easy to set up the real problem within the f... more In solving the real-world transport tasks, it is not easy to set up the real problem within the frames of mathematically defined vehicle routing problems (VRP). There are also difficulties in selecting the algorithm that could give the optimal solution of the classified problem. Using the real vehicle routing problem six constructive algorithms were developed and for each algorithm five optimisations i.e. local searches were performed. All calculations were made by using the interactive software environment Venera, and the algorithms were written in the programming language Mars. The solutions have been assessed and inter-compared by means of analytic hierarchy process. For the same problem, the location of the depot in relation to the user cluster was changed. Six mentioned algorithms were performed on the newly created problem, and the newly obtained solutions were analyzed in relation to the previous location of the depot. The following factors were taken into consideration: the number of vehicles, the time necessary to calculate the route and the overall travelled distance of the vehicle fleet. It has been determined that there is dependence of the solutions obtained by certain algorithms regarding the location of the depot with regard to the customers as well as the possibility of achieving savings by changing the location of the depot.
This paper presents a case study on organization of pre-trip route planning and clustering for sa... more This paper presents a case study on organization of pre-trip route planning and clustering for sales activity. Pre-trip route planning is a standard service of intelligent transportation systems (ITS). The study observed the territory of the Republic of Croatia which is represented with historical data for 16 515 points of sales. The solution should discover the number of sales regions, number of salesmen per region and planned routes for a single month. Constraints and input data are derived from real life points of sales data like sales potentials, geographic position and maximum number of customers for each route.
The globalisation of the economy leads to a rapidly growing exchange of goods on our planet. Limi... more The globalisation of the economy leads to a rapidly growing exchange of goods on our planet. Limited commodities and transportation resources, high planning complexity and the increasing cost pressure through the strong competition between logistics service providers make it essential to use computer-aided systems for the planning of the transports. An important subtask in this context is the operational planning of trucks or other specialized transportation vehicles. These optimization tasks are called Vehicle Routing Problems (VRP). Over 1000 papers about a huge variety of Vehicle Routing Problems indicate the practical and theoretical importance of this NP-hard optimization problem. Therefore, many specific solvers for different Vehicle Routing Problems can be found in the literature. The drawback is that most of these solvers are high specialized and inflexible and it needs a lot of effort to adapt them to modified problems. Additionally, most real world problems are often much more complex than the idealized problems out of literature and they also change over time. To face this issue, we present an integrated modelling and optimization framework for solving complex and practical relevant Vehicle Routing Problems. The modular structure of the framework, a script based modelling language, a library of VRP related algorithms and a graphical user interface give the user both reusable components and high flexibility for rapid prototyping of complex Vehicle Routing Problems.
Transport logistics and fleet management problems often fall into one class of the optimization p... more Transport logistics and fleet management problems often fall into one class of the optimization problems. Finding an optimal set of routes for group of vehicles in the transport network under defined constraints is known as the Vehicle Routing Problem (VRP). VRP represents the NP hard problem. Solving of the VRP problem can be shortened by parallelization of the time critical steps of the sequential algorithm, decomposition of the problem and distribution of its search space among the processors or by concurrent search with different amounts of synchronism and cooperation among sub-problems. The paper presents the description of the developed VRP solving system Venera/Mars and the discussion of results obtained by the implementation of the heuristic algorithms for solving the practical VRP problems in city logistics.
ABSTRACT We present two hybrid Metaheuristics, a hybrid Iterated Local Search and a hybrid Simula... more ABSTRACT We present two hybrid Metaheuristics, a hybrid Iterated Local Search and a hybrid Simulated Annealing, for solving real-world extensions of the Vehicle Routing Problem with Time Windows. Both hybrid Metaheuristics are based on the same neighborhood generating operators and local search procedures. The initial solutions are obtained by the Coefficient Weighted Distance Time Heuristics with automated parameter tuning. The strategies are compared in an empirical study on four real-world problems. A performance measure is used that also considers multiple restarts of the algorithms.
In order to solve the practical Vehicle Routing Problems (VRP) by heuristic methods, the programm... more In order to solve the practical Vehicle Routing Problems (VRP) by heuristic methods, the programming language Mars and the interactive program environment Venera have been developed and implemented. The implementation and verification of the heuristic algorithms will be improved by the application of new network (cluster/grid) technologies and by adapting Mars and Venera for the distributed and parallel method of operation.
Proceedings of the 11th World International …, 2004
The Vehicle Routing Problem is a difficult combinatorial optimization task which needs to be exte... more The Vehicle Routing Problem is a difficult combinatorial optimization task which needs to be extended for solving practical problems in the sense of constraints, traffic rules and metrics.
Vehicle routing problems with time windows (VRPTW) represent hard combinatorial problems which ar... more Vehicle routing problems with time windows (VRPTW) represent hard combinatorial problems which are in practice usually solved by heuristic and meta-heuristic methods. The principle of solving the VRPTW problems has been described by means of two heuristic methods of which the former one serves to obtain the initial feasible solution, and the latter for its further improvement. The algorithms have been implemented and tested in the developed programming language Mars which facilitates the writing of algorithms for solving VRP problems. In order to speed up the problem solving procedure, the instructions for support to distributed writing of algorithms have been included in the programming language. The concept of distributing CWTDH and Lambda local search algorithms has been presented as well as, solutions of standard test examples from literature, and comparative results of computation times depending on the number of nodes included in the computation.
Proceedings of the Congress ITS in Europe" …, 2004
The solving of Vehicle Routing Problem (VRP) is a difficult combinatorial optimisation task. The ... more The solving of Vehicle Routing Problem (VRP) is a difficult combinatorial optimisation task. The interactive programming environment Venera and programming language Mars, oriented to ease the build up of constructive heuristic algorithms for VRP, have been developed. The structure and functionality of programming environment and programming language are described.
Vehicle routing problems (VRP) are very difficult combinatorial problems which in practice often ... more Vehicle routing problems (VRP) are very difficult combinatorial problems which in practice often require modifications of the existing algorithms and development of new ideas in order to obtain suitable solutions within acceptable periods of time. The programming language Mars with routing oriented built-in data types and instructions has been conceived in such a way as to enable fast development and testing of constructive and heuristic algorithms intended for solving the VRP group of problems. Development of the language has been directed towards easier writing of (meta)heuristic algorithms, distributed and parallel execution of the algorithms in the cluster/grid environment and assistance in practical VRP problem solving.
In the field of vehicle routing, relatively limited attention has been paid to the topics such as... more In the field of vehicle routing, relatively limited attention has been paid to the topics such as stochastic demand. With the data warehouse infrastructure and data mining tools it is possible to predict such variable constraints. This could enable more efficient route construction and as consequence the number of non accomplished routes could be reduced. The paper proposes database infrastructure, data mining module and VRP solver for prediction of uncertain demand. Proposed VRP solver uses constructive, heuristic and metaheuristic algorithms to solve a problem with demanded data.
Time Windows (VRPTW) and shows that implementing algorithms for solving various instances of VRPs... more Time Windows (VRPTW) and shows that implementing algorithms for solving various instances of VRPs can significantly reduce transportation costs that occur during the delivery process. Two metaheuristic algorithms were developed for solving VRPTW: Simulated Annealing and Iterated Local Search. Both algorithms generate initial feasible solution using constructive heuristics and use operators and various strategies for an iterative improvement. The algorithms were tested on Solomon's benchmark problems and real world vehicle routing problems with time windows. In total, 44 real world problems were optimized in the case study using described algorithms. Obtained results showed that the same distribution task can be accomplished with savings up to 40% in the total travelled distance and that manually constructed routes are very ineffective.
In solving the real-world transport tasks, it is not easy to set up the real problem within the f... more In solving the real-world transport tasks, it is not easy to set up the real problem within the frames of mathematically defined vehicle routing problems (VRP). There are also difficulties in selecting the algorithm that could give the optimal solution of the classified problem. Using the real vehicle routing problem six constructive algorithms were developed and for each algorithm five optimisations i.e. local searches were performed. All calculations were made by using the interactive software environment Venera, and the algorithms were written in the programming language Mars. The solutions have been assessed and inter-compared by means of analytic hierarchy process. For the same problem, the location of the depot in relation to the user cluster was changed. Six mentioned algorithms were performed on the newly created problem, and the newly obtained solutions were analyzed in relation to the previous location of the depot. The following factors were taken into consideration: the number of vehicles, the time necessary to calculate the route and the overall travelled distance of the vehicle fleet. It has been determined that there is dependence of the solutions obtained by certain algorithms regarding the location of the depot with regard to the customers as well as the possibility of achieving savings by changing the location of the depot.
This paper presents a case study on organization of pre-trip route planning and clustering for sa... more This paper presents a case study on organization of pre-trip route planning and clustering for sales activity. Pre-trip route planning is a standard service of intelligent transportation systems (ITS). The study observed the territory of the Republic of Croatia which is represented with historical data for 16 515 points of sales. The solution should discover the number of sales regions, number of salesmen per region and planned routes for a single month. Constraints and input data are derived from real life points of sales data like sales potentials, geographic position and maximum number of customers for each route.
The globalisation of the economy leads to a rapidly growing exchange of goods on our planet. Limi... more The globalisation of the economy leads to a rapidly growing exchange of goods on our planet. Limited commodities and transportation resources, high planning complexity and the increasing cost pressure through the strong competition between logistics service providers make it essential to use computer-aided systems for the planning of the transports. An important subtask in this context is the operational planning of trucks or other specialized transportation vehicles. These optimization tasks are called Vehicle Routing Problems (VRP). Over 1000 papers about a huge variety of Vehicle Routing Problems indicate the practical and theoretical importance of this NP-hard optimization problem. Therefore, many specific solvers for different Vehicle Routing Problems can be found in the literature. The drawback is that most of these solvers are high specialized and inflexible and it needs a lot of effort to adapt them to modified problems. Additionally, most real world problems are often much more complex than the idealized problems out of literature and they also change over time. To face this issue, we present an integrated modelling and optimization framework for solving complex and practical relevant Vehicle Routing Problems. The modular structure of the framework, a script based modelling language, a library of VRP related algorithms and a graphical user interface give the user both reusable components and high flexibility for rapid prototyping of complex Vehicle Routing Problems.
Transport logistics and fleet management problems often fall into one class of the optimization p... more Transport logistics and fleet management problems often fall into one class of the optimization problems. Finding an optimal set of routes for group of vehicles in the transport network under defined constraints is known as the Vehicle Routing Problem (VRP). VRP represents the NP hard problem. Solving of the VRP problem can be shortened by parallelization of the time critical steps of the sequential algorithm, decomposition of the problem and distribution of its search space among the processors or by concurrent search with different amounts of synchronism and cooperation among sub-problems. The paper presents the description of the developed VRP solving system Venera/Mars and the discussion of results obtained by the implementation of the heuristic algorithms for solving the practical VRP problems in city logistics.
ABSTRACT We present two hybrid Metaheuristics, a hybrid Iterated Local Search and a hybrid Simula... more ABSTRACT We present two hybrid Metaheuristics, a hybrid Iterated Local Search and a hybrid Simulated Annealing, for solving real-world extensions of the Vehicle Routing Problem with Time Windows. Both hybrid Metaheuristics are based on the same neighborhood generating operators and local search procedures. The initial solutions are obtained by the Coefficient Weighted Distance Time Heuristics with automated parameter tuning. The strategies are compared in an empirical study on four real-world problems. A performance measure is used that also considers multiple restarts of the algorithms.
In order to solve the practical Vehicle Routing Problems (VRP) by heuristic methods, the programm... more In order to solve the practical Vehicle Routing Problems (VRP) by heuristic methods, the programming language Mars and the interactive program environment Venera have been developed and implemented. The implementation and verification of the heuristic algorithms will be improved by the application of new network (cluster/grid) technologies and by adapting Mars and Venera for the distributed and parallel method of operation.
Proceedings of the 11th World International …, 2004
The Vehicle Routing Problem is a difficult combinatorial optimization task which needs to be exte... more The Vehicle Routing Problem is a difficult combinatorial optimization task which needs to be extended for solving practical problems in the sense of constraints, traffic rules and metrics.
Vehicle routing problems with time windows (VRPTW) represent hard combinatorial problems which ar... more Vehicle routing problems with time windows (VRPTW) represent hard combinatorial problems which are in practice usually solved by heuristic and meta-heuristic methods. The principle of solving the VRPTW problems has been described by means of two heuristic methods of which the former one serves to obtain the initial feasible solution, and the latter for its further improvement. The algorithms have been implemented and tested in the developed programming language Mars which facilitates the writing of algorithms for solving VRP problems. In order to speed up the problem solving procedure, the instructions for support to distributed writing of algorithms have been included in the programming language. The concept of distributing CWTDH and Lambda local search algorithms has been presented as well as, solutions of standard test examples from literature, and comparative results of computation times depending on the number of nodes included in the computation.
Proceedings of the Congress ITS in Europe" …, 2004
The solving of Vehicle Routing Problem (VRP) is a difficult combinatorial optimisation task. The ... more The solving of Vehicle Routing Problem (VRP) is a difficult combinatorial optimisation task. The interactive programming environment Venera and programming language Mars, oriented to ease the build up of constructive heuristic algorithms for VRP, have been developed. The structure and functionality of programming environment and programming language are described.
Vehicle routing problems (VRP) are very difficult combinatorial problems which in practice often ... more Vehicle routing problems (VRP) are very difficult combinatorial problems which in practice often require modifications of the existing algorithms and development of new ideas in order to obtain suitable solutions within acceptable periods of time. The programming language Mars with routing oriented built-in data types and instructions has been conceived in such a way as to enable fast development and testing of constructive and heuristic algorithms intended for solving the VRP group of problems. Development of the language has been directed towards easier writing of (meta)heuristic algorithms, distributed and parallel execution of the algorithms in the cluster/grid environment and assistance in practical VRP problem solving.
In the field of vehicle routing, relatively limited attention has been paid to the topics such as... more In the field of vehicle routing, relatively limited attention has been paid to the topics such as stochastic demand. With the data warehouse infrastructure and data mining tools it is possible to predict such variable constraints. This could enable more efficient route construction and as consequence the number of non accomplished routes could be reduced. The paper proposes database infrastructure, data mining module and VRP solver for prediction of uncertain demand. Proposed VRP solver uses constructive, heuristic and metaheuristic algorithms to solve a problem with demanded data.
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Papers by Tonci Caric