Herbert Kopfer

Horizontal cooperation among freight carriers: request allocation and profit sharing

In modern transportation systems, the potential for further decreasing the costs of fulfilling customer requests is severely limited while market competition is constantly reducing revenues. However, increased competitiveness through cost reductions can be achieved if freight carriers cooperate in order to balance their request portfolios. Participation in such coalitions can benefit the entire coalition, as well as each participant individually, thus reinforcing the market position of the partners. The work presented in this paper uniquely combines features of routing and scheduling problems and of cooperative game theory. In the first part, the profit margins resulting from horizontal cooperation among freight carriers are analysed. It is assumed that the structure of customer requests corresponds to that of a pickup and delivery problem with time windows for each freight carrier. In the second part, the possibilities of sharing these profit margins fairly among the partners are discussed. The Shapley value can be used to determine a fair allocation. Numerical results for real-life and artificial instances are presented.

On Permutation Representations for Scheduling Problems

In this paper we concentrate on job shop scheduling as a representative of constrained combinatorial problems. We introduce a new permutation representation for this problem. Three crossover operators, different in tending to preserve the relative order, the absolute order, and the position in the permutation, are defined. By experiment we observe the strongest phenotypical correlation between parents and offspring when respecting the absolute order. It is shown that a genetic algorithm using an operator which preserves the absolute order also obtains a superior solution quality.

Collaborating freight forwarding enterprises

The paper presents a model for the collaboration among independent freight forwarding entities. In the modern highly competitive transportation branch freight forwarders reduce their fulfillment costs by exploiting different execution modes (self-fulfillment and subcontraction). For self-fulfillment they use their own vehicles to execute the requests and for subcontracting they forward the orders to external freight carriers. Further enhancement of competitiveness can be achieved if the freight forwarders cooperate in coalitions in order to balance their request portfolios. Participation in such a coalition gains additional profit for the entire coalition and for each participant, therefore reinforcing the market position of the partners. The integrated operational transport problem as well as existing collaboration approaches are introduced. The presented model for collaboration is based on theoretical foundations in the field of combinatorial auctions and operational research game theory. It is applicable for coalitions of freight forwarders, especially for the collaboration of Profit Centres within large freight forwarding companies. The proposed theoretical approach and the presented collaboration model are suitable for a coalition of freight forwarding companies with nearly similar potential on the market.

Distributed Decision Making in Combined Vehicle Routing and Break Scheduling

The problem of combined vehicle routing and break scheduling comprises three subproblems: clustering of customer requests, routing of vehicles, and break scheduling. In practice, these subproblems are usually solved in the interaction between planners and drivers. We consider the case that the planner performs the clustering and the drivers perform the routing and break scheduling. To analyze this problem, we embed it into the framework of distributed decision making proposed by Schneeweiss (Eur J Oper Res 150(2):237–252, 2003). We investigate two different degrees of anticipation of the drivers’ planning behaviour using computational experiments. The results indicate that in this application a more precise anticipation function results in better objective values for both the planner and the drivers.

Heuristic-based truck scheduling for inland container transportation

A truck scheduling problem for container transportation in a local area with multiple depots and multiple terminals including containers as a resource for transportation is addressed. Four types of movements of containers as inbound full, outbound full, inbound empty and outbound empty movements as well as the time windows at both the origin and the destination are considered. The total operating time of all trucks in operation is taken as the optimization criterion that has to be minimized. The problem is mathematically modeled based on a preparative graph formulation and falls into an extension of the multiple traveling salesman problem with time windows (m-TSPTW). The window partition based solution method for the m-TSPTW in Wang and Regan (Transp Res Part B: Methodol 36:97–112, 2002) is modified so that its computation time is reduced greatly. The experiments based on a number of randomly generated instances indicate that the modified method is quite fast and the quality of solutions is relatively high for the m-TSPTW. These experiments also demonstrate that our approach is able to generate high-quality results for the equivalent truck scheduling and inland container movement problem in container drayage operations.

Collaborative transportation planning of less-than-truckload freight

Collaborative transportation planning (CTP) within a coalition of small and medium-sized freight carriers can be used as a powerful instrument to improve the operational efficiency of the coalition members. In such coalitions, transportation requests from different carriers are exchanged in order to reduce the total fulfillment costs. In this paper, the CTP for a set of independent carriers exchanging less-than-truckload transportation requests is considered. The realistic restriction that all collaborating partners have only limited capacities in their fleets is included in the consideration. To keep their autonomy, coalition members keep their sensitive information including customer payments and cost structures unexposed during CTP. A new decentralized request exchange mechanism for CTP is proposed while only vehicle routes are considered for exchange. It is tested on some newly generated instances and the CTP solutions are compared with those obtained by isolated planning without collaboration and those obtained by a heuristic approach for the centralized planning problem. The results indicate that our mechanism is very efficient and effective in terms of realizing potential cost-savings by CTP, even when capacity limitations and restrictions on the exposure of information are explicitly considered.

A search space analysis of the Job Shop Scheduling Problem

A computational study for the Job Shop Scheduling Problem is presented. Thereby,emphasis is put on the structure of the search space as it appears for local search. A statisticalanalysis of the search space reveals the impact of inherent properties of the problem onlocal search based heuristics.

Transportation planning in freight forwarding companies: Tabu search algorithm for the integrated operational transportation planning problem

The integrated operational transportation planning problem extends the traditional vehicle routing and scheduling problem by the possibility of outsourcing a part of the requests by involving subcontractors. The purpose of this paper is to present the integrated planning problem and to propose an approach for solving it by a tabu search heuristic. Existing approaches from literature which discuss vehicle routing combined with outsourcing regard only one specific type of subcontracting. This paper describes and explores the complex situation where an own fleet and several types of subcontracting are used for request fulfillment. As the approach contains new aspects, unknown to the literature so far, tabu search is extended to special types of moves. On the basis of computational results the cost structure is analyzed in order to investigate the long-term planning question whether and to what extend it is profitable to maintain an own fleet.

Control of Parallel Population Dynamics by Social-Like Behavior of GA-Individuals

A frequently observed difficulty in the application of genetic algorithms to the domain of optimization arises from premature convergence. In order to preserve genotype diversity we develop a new model of auto-adaptive behavior for individuals. In this model a population member is an active individual that assumes social-like behavior patterns. Different individuals living in the same population can assume different patterns. By moving in a hierarchy of “social states” individuals change their behavior. Changes of social state are controlled by arguments of plausibility. These arguments are implemented as a rule set for a massively-parallel genetic algorithm. Computational experiments on 12 large-scale job shop benchmark problems show that the results of the new approach dominate the ordinary genetic algorithm significantly.

Operational transportation planning of freight forwarding companies in horizontal coalitions

In order to improve profitability, freight forwarding companies try to organize their operational transportation planning systematically, considering not only their own fleet but also external resources. Such external resources include vehicles from closely related subcontractors in vertical cooperations, autonomous common carriers on the transportation market, and cooperating partners in horizontal coalitions. In this paper, the transportation planning process of forwarders is studied and the benefit of including external resources is analyzed. By introducing subcontracting, the conventional routing of own vehicles is extended to an integrated operational transportation planning, which simultaneously constructs fulfillment plans with overall lowest costs using the own fleet and subcontractors’ vehicles. This is then combined with planning strategies, which intend to increase the profitability by exchanging requests among members in horizontal coalitions. Computational results show considerable cost reductions using the proposed planning approach.