A continuous-time MILP model for short-term scheduling of make-and-pack production processes

In process industries, make-and-pack production is used to produce food and beverages, chemicals, and metal products, among others. This type of production process allows the fabrication of a wide range of products in relatively small amounts using the same equipment. In this article, we consider a real-world production process (cf. Honkomp et al. 2000. The curse of reality – why process scheduling optimization problems are diffcult in practice. Computers & Chemical Engineering, 24, 323–328.) comprising sequence-dependent changeover times, multipurpose storage units with limited capacities, quarantine times, batch splitting, partial equipment connectivity, and transfer times. The planning problem consists of computing a production schedule such that a given demand of packed products is fulfilled, all technological constraints are satisfied, and the production makespan is minimised. None of the models in the literature covers all of the technological constraints that occur in such make-and-pack production processes. To close this gap, we develop an efficient mixed-integer linear programming model that is based on a continuous time domain and general-precedence variables. We propose novel types of symmetry-breaking constraints and a preprocessing procedure to improve the model performance. In an experimental analysis, we show that small- and moderate-sized instances can be solved to optimality within short CPU times.

Optimal Scheduling of Work-Content-Constrained Projects

The execution of a project requires resources that are generally scarce. Classical approaches to resource allocation assume that the usage of these resources by an individual project activity is constant during the execution of that activity; in practice, however, the project manager may vary resource usage over time within prescribed bounds. This variation gives rise to the project scheduling problem which consists in allocating the scarce resources to the project activities over time such that the project duration is minimized, the total number of resource units allocated equals the prescribed work content of each activity, and various work-content-related constraints are met. We formulate this problem for the first time as a mixed-integer linear program. Our computational results for a standard test set from the literature indicate that this model outperforms the state-of-the-art solution methods for this problem.

Experimental characterization of cement–bentonite interaction using core infiltration techniques and 4D computed tomography

Deep geological storage of radioactive waste foresees cementitious materials as reinforcement of tunnels and as backfill. Bentonite is proposed to enclose spent fuel drums, and as drift seals. The emplacement of cementitious material next to clay material generates an enormous chemical gradient in pore water composition that drives diffusive solute transport. Laboratory studies and reactive transport modeling predict significant mineral alteration at and near interfaces, mainly resulting in a decrease of porosity in bentonite. The goal of this project is to characterize and quantify the cement/bentonite skin effects spatially and temporally in laboratory experiments. A newly developed mobile X-ray transparent core infiltration device was used, which allows performing X-ray computed tomography (CT) periodically without interrupting a running experiment. A pre-saturated cylindrical MX-80 bentonite sample (1920 kg/m3 average wet density) is subjected to a confining pressure as a constant total pressure boundary condition. The infiltration of a hyperalkaline (pH 13.4), artificial OPC (ordinary Portland cement) pore water into the bentonite plug alters the mineral assemblage over time as an advancing reaction front. The related changes in X-ray attenuation values are related to changes in phase densities, porosity and local bulk density and are tracked over time periodically by non-destructive CT scans.