Simulation Optimization for the Stochastic Economic Lot Scheduling Problem with Sequence-Dependent Setup Times

We consider the stochastic economic lot scheduling problem (SELSP) with lost sales and random demand, where switching between products is subject to sequence-dependent setup times. We propose a solution based on simulation optimization using an iterative two-step procedure which combines global policy search with local search heuristics for the traveling salesman sequencing subproblem. To optimize the production cycle, we compare two criteria: minimizing total setup times and evenly distributing setups to obtain a more regular production cycle. Based on a numerical study, we find that a policy with a balanced production cycle leads to lower cost than other policies with unbalanced cycles. (authors' abstract

Retail Warehouse Loading Dock Coordination by Core-selecting Package Auctions

Congestions at loading docks can cause severe delays in logistics processes and cause increasing bottlenecks for truck routes. For warehouses, uncoordinated arrivals of trucks make appropriate staffing difficult and congestions can interfere with other processes at the facility. To mitigate congestions at loading docks, we propose package auctions to allocate time slots to trucks. \ \ The contribution of this research is the application of core-selecting package auctions to address the loading dock congestion problem. We propose a bidding language and a core-selecting package auction for this setting based on existing literature. Core-selecting payment rules can avoid drawbacks of the Vickrey–Clarke–Groves (VCG) mechanism with Clarke pivot rule, e.g., low perceived fairness of prices. \ \ We evaluate our proposal by means of simulation and assess (i) the potential for waiting time reduction compared to uncoordinated arrivals as well as sharing of historical waiting times, (ii) the empirical complexity of the computational problem for scenarios of varying complexity, and (iii) the relation of VCG and bidder-Pareto-optimal core payments. Our findings provide evidence that loading dock auctions can alleviate congestion substantially and that the core-pricing rule is well-suited to address the price fairness and low seller revenue problems in this setting

Sonoco uses a stochastic lotsizing and scheduling model to optimize the production of coreboard

Since several years we have been working together with the European supply chain team of Sonoco, one of the largest global players active in the packaging industry, to solve a variety of supply chain challenges encountered in their industrial products & services division. In this work, we present the result from a pilot project related to production planning for which we developed a novel stochastic lotsizing and scheduling model and a solution approach tailored to their specific business environment

A linearization approach to the stochastic dynamic capacitated lotsizing problem with sequence-dependent changeovers

Inspired by the production and planning process of coreboard of our industry partner, a Fortune 1000 player in packaging, we present a mixed-integer linear programming model that can jointly optimize lot sizes, production sequences and safety stocks in the presence of sequence-dependent changeovers. First, we formulate a nonlinear (MINLP) model that can handle both the stochasticity and the sequence-dependency of the stochastic dynamic capacitated lotsizing problem, based on the stochastic sequence-independent (Tempelmeier et al. 2018) and deterministic sequence-dependent (Guimaraes et al. 2014) version of the problem. Then, we develop a piecewise linearization approach for the non-linear inventory on hand and backorder curves that builds on and challenges earlier research published by van Pelt and Fransoo 2018 and Tempelmeier et al. 2018. We use the derivatives of the inventory on hand and backorder functions to develop a tailored breakpoint selection strategy that reduces the maximum approximation error between the linearized and non-linear objective function from 20.3% to 0.5% in comparison to the equidistant linearization strategy recommend by the aforementioned articles. As a third and last contribution, we develop a Relax-and-Fix with Fix-andOptimize heuristic and show in an extensive numerical study that it improved the objective value by 20% on average and realized an average run time reduction of 60% over a state-of-the-art solver

Interleukin-22 Is Frequently Expressed in Small- and Large-Cell Lung Cancer and Promotes Growth in Chemotherapy-Resistant Cancer Cells

Introduction: In lung cancer, interleukin-22 (IL-22) expression within primary tissue has been demonstrated, but the frequency and the functional consequence of IL-22 signaling have not been addressed. This study aims at analyzing the cellular effects of IL-22 on lung carcinoma cell lines and the prognostic impact of IL-22 tissue expression in lung cancer patients. Methods: Biological effects of IL-22 signaling were investigated in seven lung cancer cell lines by Western blot, flow cytometry, real-time polymerase chain reaction, and proliferation assays. Tumor tissue specimens of two cohorts with a total of 2300 lung cancer patients were tested for IL-22 expression by immunohistochemistry. IL-22 serum concentrations were analyzed in 103 additional patients by enzyme-linked immunosorbent assay. Results: We found the IL-22 receptor 1 (IL-22-R1) to be expressed in six of seven lung cancer cell lines. However IL-22 signaling was functional in only four cell lines, where IL-22 induced signal transducer activator of transcription 3 phosphorylation and increased cell proliferation. Furthermore, IL-22 induced the expression of antiapoptotic B-cell lymphoma 2, but did not rescue tumor cells from carboplatin-induced apoptosis. Cisplatin-resistant cell lines showed a significant up-regulation of IL-22-R1 along with a stronger proliferative response to IL-22 stimulation. IL-22 was preferentially expressed in small- and large-cell lung carcinoma (58% and 46% of cases, respectively). However, no correlation between IL-22 expression by immunohistochemistry and prognosis was observed. Conclusion: IL-22 is frequently expressed in lung cancer tissue. Enhanced IL-22-R1 expression and signaling in chemotherapy-refractory cell lines are indicative of a protumorigenic function of IL-22 and may contribute to a more aggressive phenotype