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In this paper, a scheduling problem that occurs in potash mining is introduced, where a block excavation sequence has to be found taking into account a limited number of underground machines as well as safety-related restrictions. The aim is to minimize the maximum completion time of excavations, i.e., the makespan. The resulting problem can be transformed into a hybrid flow shop scheduling problem with reentry, unrelated machines, and job-precedences. A mixed-integer linear model is presented and small-scale instances are solved with CPLEX. In order to tackle medium- and large-scale instances heuristically, a basic and an advanced multi-start algorithm are developed, based on a specific priority rule-based construction procedure. In addition, a modified version of the Giffler and Thompson procedure is applied. Computational experiments are conducted on problem instances derived from real-world data in order to evaluate the performances of the proposed solution procedures. [ABSTRACT FROM AUTHOR]

Resource leveling problems arise whenever it is expedient to reduce the fluctuations in resource utilization over time, while maintaining a prescribed project completion deadline. Several resource leveling objective functions may be defined, consideration of which results in well-balanced resource profiles. In this paper, we concentrate on a special objective function that determines the costs arising from increasing or decreasing the resource utilizations. The resulting total adjustment cost problem occurs, for example, in the construction industry and can be formulated using mixed-integer linear programming models. Apart from a discrete time-based formulation, two polynomial formulations, namely an event-based model and a start-based model, which exploit structural properties of the problem are presented. In addition, a heuristic solution algorithm is proposed to generate start solutions for the problem. We use CPLEX 12.4 to solve medium-scale instances known from the literature. A computational performance analysis shows that the discrete time-based model and the start-based model are suitable for practical applications. [ABSTRACT FROM AUTHOR]

In reverse logistics networks, products (e.g., bottles or containers) have to be transported from a depot to customer locations and, after use, from customer locations back to the depot. In order to operate economically beneficial, companies prefer a simultaneous delivery and pick-up service. The resulting Vehicle Routing Problem with Simultaneous Delivery and Pick-up (VRPSDP) is an operational problem, which has to be solved daily by many companies. We present two mixed-integer linear model formulations for the VRPSDP, namely a vehicle-flow and a commodity-flow model. In order to strengthen the models, domain-reducing preprocessing techniques, and effective cutting planes are outlined. Symmetric benchmark instances known from the literature as well as new asymmetric instances derived from real-world problems are solved to optimality using CPLEX 12.1. [ABSTRACT FROM AUTHOR]