A Sequential Workforce Scheduling and Routing Problem for the Retail Industry: A Case Study

This study investigated the operational workforce scheduling and routing problem of a leading international retail company. Currently, the company plans to launch a new product into the Turkish market, which will be used in all its retail stores across the country. For the best marketing outcome, branding of all retail stores needs to be renewed by an outsourced workforce with a minimum of cost and time. We framed this as a workforce scheduling and routing optimization problem. Therefore, a two-stage solution was proposed. The retail stores were partitioned into disjoint regions in the first stage, and the schedules were optimized in the second stage. We employed the k-means clustering algorithm for constructing these regions. Two different heuristic approaches were applied to solve regional scheduling in the second stage of the algorithm since the resulting scheduling problem is NP-hard. Finally, a computational analysis was performed with real data and the results are discussed

Variable neighborhood search-based algorithms for the parallel machine capacitated lot-sizing and scheduling problem

This paper addresses the capacitated lot-sizing and scheduling problem on parallel machines with eligibility constraints, sequence-dependent setup times, and costs. The objective is to find a production plan that minimizes production, setup, and inventory holding costs while meeting the demands of products for each period without delay for a given planning horizon. Since the studied problem is NP-hard, we proposed metaheuristic approaches, Variable Neighborhood Search, Variable Neighborhood Descent, and Reduced Variable Neighborhood Search algorithms to analyze their performance on the problem. Initially, we presented an initial solution generation method to satisfy each period's demand. Then, we defined insert, swap, and fractional insert moves for generating neighborhood solutions. We employed an adaptive constraint handling technique to enlarge the search space by accepting infeasible solutions during the search. Lastly, we performed computational experiments over the benchmark instances. The computational results show the effectiveness of the proposed solution approaches, compared to existing solution techniques in the literature, and the improvements in various problem instances compared to the best-known results

Cargo allocation and vessel scheduling on liner shipping with synchronization of transshipments

A mixed integer linear programming model is presented for the operational level cargo allocation and vessel scheduling problem of a liner shipping company in Turkey, where flow-dependent port-stay lengths, transit times and transshipment synchronizations are considered. The proposed model aims to assign shipments to routes to decrease total tardiness and construct partial vessel schedules for establishing coordination with port authorities to comply with the berthing time windows. In addition to the mathematical model, novel valid inequalities and benders decomposition algorithm are implemented. Performance of the developed algorithm is evaluated on real-life problem instances. The results show that benders decomposition with valid inequalities yields the best performance. (C) 2019 Elsevier Inc. All rights reserved.Project Evaluation Commission of Yasar University [BAP038]This work was supported within the scope of the scientific research project which was accepted by the Project Evaluation Commission of Yasar University under the project number BAP038 and title Solution Approaches for the Integrated Liner Shipping Network Design and Container Terminal Operations

Daily Production Planning Problem of an International Energy Management Company

This study is about real-life production and capacity planning problem in an international company which operates in energy management sector in Manisa, Turkey. The company produces different types of circuit breakers and delivers its products to different countries and distribution center, located in France. Within the scope of this problem, the production plan is done for nine products that are manufactured on six production lines. Each product has a unique production line, but some of the products are processed on common production lines. In this study, the production lot amount is determined each day by considering the due date and quantity of the customer orders without exceeding the capacity of the production lines. In the existing system, there are many tardy and early customer orders and the production plan is done manually which causes time loss for the company. A preemptive goal programming model is proposed for solving this problem where the main goal is to minimize total lateness in customer orders and minimizing the number of customer orders that have been split is considered as the secondary objective. The proposed mathematical model is solved optimally for real life instances in IBM ILOG CPLEX Optimization Studio 12.6.3. In addition, a heuristic method is presented in order to decrease the daily production planning duration and the fulfill the company’s needs. Moreover, a user-friendly decision support system is developed where both solution techniques are embedded.</p

Genetic regulation of immunoglobulin E level in different pathological states: integration of mouse and human genetics

Immunoglobulin E (IgE) first evolved in mammals. It plays an important role in defence against helminths and parasitic infection and in pathological states including allergic reactions, anti-tumour defence and autoimmune diseases. Elucidation of genetic control of IgE level could help us to understand regulation of the humoral immune response in health and disease, the etiology and pathogenesis of many human diseases, and to facilitate discovery of more effective methods for their prevention and cure. Herein we summarise progress in the genetics of regulation of IgE level in human diseases and show that integration of different approaches and use of animal models have synergistic effects in gaining new knowledge about both protective and pathological roles of this important antibody

Evaluation of a quality improvement intervention to reduce anastomotic leak following right colectomy (EAGLE): pragmatic, batched stepped-wedge, cluster-randomized trial in 64 countries

Background Anastomotic leak affects 8 per cent of patients after right colectomy with a 10-fold increased risk of postoperative death. The EAGLE study aimed to develop and test whether an international, standardized quality improvement intervention could reduce anastomotic leaks. Methods The internationally intended protocol, iteratively co-developed by a multistage Delphi process, comprised an online educational module introducing risk stratification, an intraoperative checklist, and harmonized surgical techniques. Clusters (hospital teams) were randomized to one of three arms with varied sequences of intervention/data collection by a derived stepped-wedge batch design (at least 18 hospital teams per batch). Patients were blinded to the study allocation. Low- and middle-income country enrolment was encouraged. The primary outcome (assessed by intention to treat) was anastomotic leak rate, and subgroup analyses by module completion (at least 80 per cent of surgeons, high engagement; less than 50 per cent, low engagement) were preplanned. Results A total 355 hospital teams registered, with 332 from 64 countries (39.2 per cent low and middle income) included in the final analysis. The online modules were completed by half of the surgeons (2143 of 4411). The primary analysis included 3039 of the 3268 patients recruited (206 patients had no anastomosis and 23 were lost to follow-up), with anastomotic leaks arising before and after the intervention in 10.1 and 9.6 per cent respectively (adjusted OR 0.87, 95 per cent c.i. 0.59 to 1.30; P = 0.498). The proportion of surgeons completing the educational modules was an influence: the leak rate decreased from 12.2 per cent (61 of 500) before intervention to 5.1 per cent (24 of 473) after intervention in high-engagement centres (adjusted OR 0.36, 0.20 to 0.64; P &lt; 0.001), but this was not observed in low-engagement hospitals (8.3 per cent (59 of 714) and 13.8 per cent (61 of 443) respectively; adjusted OR 2.09, 1.31 to 3.31). Conclusion Completion of globally available digital training by engaged teams can alter anastomotic leak rates. Registration number: NCT04270721 (http://www.clinicaltrials.gov)