An MILP-based heuristic for staff scheduling problems with acceptance levels

We present a real-world staff-assignment problem that was reported to us by a provider of an online workforce scheduling software. The problem consists of assigning employees to work shifts subject to a large variety of requirements related to work laws, work shift compatibility, workload balancing, and personal preferences of employees. A target value is given for each requirement, and all possible deviations from these values are associated with acceptance levels. The objective is to minimize the total number of deviations in ascending order of the acceptance levels. We present an exact lexicographic goal programming MILP formulation and an MILP-based heuristic. The heuristic consists of two phases: in the first phase a feasible schedule is built and in the second phase parts of the schedule are iteratively re-optimized by applying an exact MILP model. A major advantage of such MILP-based approaches is the flexibility to account for additional constraints or modified planning objectives, which is important as the requirements may vary depending on the company or planning period. The applicability of the heuristic is demonstrated for a test set derived from real-world data. Our computational results indicate that the heuristic is able to devise optimal solutions to non-trivial problem instances, and outperforms the exact lexicographic goal programming formulation on medium- and large-sized problem instances.

A hybrid method for large-scale short-term scheduling of make-and-pack production processes

Due to the ongoing trend towards increased product variety, fast-moving consumer goods such as food and beverages, pharmaceuticals, and chemicals are typically manufactured through so-called make-and-pack processes. These processes consist of a make stage, a pack stage, and intermediate storage facilities that decouple these two stages. In operations scheduling, complex technological constraints must be considered, e.g., non-identical parallel processing units, sequence-dependent changeovers, batch splitting, no-wait restrictions, material transfer times, minimum storage times, and finite storage capacity. The short-term scheduling problem is to compute a production schedule such that a given demand for products is fulfilled, all technological constraints are met, and the production makespan is minimised. A production schedule typically comprises 500–1500 operations. Due to the problem size and complexity of the technological constraints, the performance of known mixed-integer linear programming (MILP) formulations and heuristic approaches is often insufficient. We present a hybrid method consisting of three phases. First, the set of operations is divided into several subsets. Second, these subsets are iteratively scheduled using a generic and flexible MILP formulation. Third, a novel critical path-based improvement procedure is applied to the resulting schedule. We develop several strategies for the integration of the MILP model into this heuristic framework. Using these strategies, high-quality feasible solutions to large-scale instances can be obtained within reasonable CPU times using standard optimisation software. We have applied the proposed hybrid method to a set of industrial problem instances and found that the method outperforms state-of-the-art methods.

Heuristic decomposition and LP-based scheduling in make-and-pack production

In this paper, we are concerned about the short-term scheduling of industrial make-and-pack production processes. The planning problem consists in minimizing the production makespan while meeting given end-product demands. Sequence-dependent changeover times, multi-purpose storage units with finite capacities, quarantine times, batch splitting, partial equipment connectivity, material transfer times, and a large number of operations contribute to the complexity of the problem. Known MILP formulations cover all technological constraints of such production processes, but only small problem instances can be solved in reasonable CPU times. In this paper, we develop a heuristic in order to tackle large instances. Under this heuristic, groups of batches are scheduled iteratively using a novel MILP formulation; the assignment of the batches to the groups and the scheduling sequence of the groups are determined using a priority rule. We demonstrate the applicability by means of a real-world production process.

Clinical and antibacterial effect of an anti-inflammatory toothpaste formulation with Scutellaria baicalensis extract on experimental gingivitis

It was the aim of the study to evaluate the clinical and antibacterial effect of a dentifrice containing an anti-inflammatory plant extract (SB) versus a placebo (PLA) using an experimental gingivitis model. Forty subjects (20 per group) discontinued all oral hygiene measures for four teeth for a period of 21 days using a shield (to generate a possible gingivitis) while they could brush the other teeth normally. After brushing, the shield was removed and teeth were treated with the randomly assigned toothpaste slurry for 1 min. Löe and Silness gingival index (GI), Silness and Löe plaque index (PI), and biofilm vitality (VF%) were assessed at days 0, 14, and 21, respectively. Subjects of the PLA group developed a GI of 0.82?±?0.342 (day 14) and 1.585?±?0.218 (day 21), while the data of the SB group were significantly reduced (0.355?±?0.243 and 0.934?±?0.342, p?formulation was able to significantly reduce the extent of gingivitis, plaque development, and vital flora.

Anti insulin-like growth factor I receptor immunoliposomes: a single formulation combining two anticancer treatments with enhanced therapeutic efficiency

Context: Through overexpression and aberrant activation in many human tumors, the IGF system plays a key role in tumor development and tumor cell proliferation. Different strategies targeting IGF-I receptor (IGFI-R) have been developed, and recent studies demonstrated that combined treatments with cytostatic drugs enhance the potency of anti-IGFI-R therapies. Objective: The objective of the study was to examine the IGFI-R expression status in neuroendocrine tumors of the gastroenteropancreatic system (GEP-NETs) in comparison with healthy tissues and use potential overexpression as a target for novel anti-IGFI-R immunoliposomes. Experimental Design: A human tumor tissue array and samples from different normal tissues were investigated by immunohistochemistry. An IGFI-R antagonistic antibody (1H7) was coupled to the surface of sterically stabilized liposomes loaded with doxorubicin. Cell lines from different tumor entities were investigated for liposomal association studies in vitro. For in vivo experiments, neuroendocrine tumor xenografts were used for evaluation of pharmacokinetic and therapeutic properties of the novel compound. Results: Immunohistochemistry revealed significant IGFI-R overexpression in all investigated GEP-NETs (n = 59; staining index, 229.1 +/- 3.1%) in comparison with normal tissues (115.7 +/- 3.7%). Furthermore, anti-IGFI-R immunoliposomes displayed specific tumor cell association (44.2 +/- 1.6% vs. IgG liposomes, 0.8 +/- 0.3%; P < 0.0001) and internalization in human neuroendocrine tumor cells in vitro and superior antitumor efficacy in vivo (life span 31.5 +/- 2.2 d vs. untreated control, 19 +/- 0.6, P = 0.008). Conclusion: IGFI-R overexpression seems to be a common characteristic of otherwise heterogenous NETs. Novel anti-IGFI-R immunoliposomes have been developed and successfully tested in a preclinical model for human GEP-NETs. Moreover in vitro experiments indicate that usage of this agent could also present a promising approach for other tumor entities.