Large-scale pickup and delivery work area design

A single‐product maritime inventory routing problem (MIRP) is studied in which the production and consumption rates vary over the planning horizon. The problem involves a heterogeneous fleet and multiple production and consumption ports with limited storage capacity. Two discrete time formulations are developed: an original model and a reformulated model that is a pure fixed charge network flow (FCNF) model with side constraints. Mixed integer sets arising from the decomposition of the formulations are identified. In particular, several lot‐sizing relaxations are derived for the formulations and used to establish valid inequalities to strengthen the proposed formulations. Until now, the derivation of models and valid inequalities for MIRPs has mainly been inspired by the developments in the routing community. Here, we have developed a new model leading to new valid inequalities for MIRPs obtained by generalizing valid inequalities from the recent lot‐sizing literature. Considering a set of instances based on real data, a computational study is conducted to test the formulations and the effectiveness of the valid inequalities. The FCNF formulation is generally much stronger than the original formulation. The developed valid inequalities reduce the integrality gap significantly for both formulations. By using a branch‐and‐bound scheme based on the strengthened FCNF formulation, most of our test instances are solved to optimality. © 2013 Wiley Periodicals, Inc. NETWORKS, Vol. 62(4), 297–314 2013

Solution method for the location planning problem of logistics park with variable capacity

Joint routing and scheduling for large-scale deterministic IP networks

We define a pickup and delivery routing problem with time windows that arises in last-mile delivery. A customer can be served either directly at home, by one of the available capacitated trucks, or via lockers, that allow a self-service option. On the same route, the couriers must deliver the parcels and collect the packages that the customers intend to return. The returned parcels can be picked up directly at the customers’ homes or at a locker. Customers can select home service, self-service at one of the nearby lockers with a discount, or let the logistics company decide. All services must be performed within a given time window.We propose three formulations, two branch-and-cut algorithms, and some valid inequalities. We also investigate the case with a single vehicle, with different types of time windows, including no time windows. Moreover, we show how to accommodate simultaneous pickup and delivery and multiple requests from a customer.

The provision of goods shuttle services sometimes faces several constraints, such as the limitation on the number of vehicles, vehicle capacity, and service time, or the vehicle used has single transport access. To avoid losses, a strategy is needed in determining the optimal route and policy for arranging goods in the vehicle especially if there are two types of goods involved. Traveling Salesman Problem and Pick-up and Delivery with Handling Costs and Time Windows (TSPPDHTW) is a model of an optimization problem that aims to minimize the total travel and goods handling costs in the goods pick-up and delivery with the constraints previously mentioned. Solving that model using the exact method requires a very long computation time so it’s not effective to be implemented in real-life. This study aims to develop a (meta)heuristic based on Ant Colony Optimization (ACO) and Tabu Search (TS) to be ACOTS to solve TSPPDHTW with reasonable computation time. The development is carried out by adding functions of clustering, evaluating constraints, cutting tours, arranging of goods, and evaluating moves on the TS, as well as modifying transition rules. The result has a deviation of about 22% and 99.99% less computational time than the exact method.

Optimised Search Heuristic Combining Valid Inequalities and Tabu Search

In recent decades, the rapid development of international economy has led to significant inter-regional trade imbalances. In marine transportation, the voluminous empty containers accumulated at ports in import dominated countries have to be re-circulated back to ports in export dominated countries for re-deployment. This repositioning of empty containers is crucial for shipping companies to provide effective transportation services. At present, empty container repositioning has proved to be highly expensive, contributing to 27% of the overall operation cost of shipping companies. Consequently, major stakeholders including the shipping companies have strived to reduce the repositioning cost. Unfortunately, few major improvements have been made over the years and there are still lingering research issues. The objective of this research, therefore, is to develop efficient and effective methodologies to obtain empty container repositioning plans that can significantly reduce transportation cost while fulfilling customer demands of empty and laden containers.
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\nIn this research, the empty container repositioning problem under two related real marine transportation scenarios has been studied. The first scenario considers multi-vessel transportation for both laden and empty containers with split vessel routing (denoted as ECRSVR). A mathematical model of ECRSVR is developed based on the formulation of the Pickup and Delivery Problem with Time Windows (PDPTW). However, a major research issue arises due to such integrated consideration of split vessel routing and transportation of empty and laden containers. The resulting model will encompass many more new decision variables and constraints. Thus, it cannot be readily solved by existing algorithms. To address this issue, a new Branch-and-Price (B&P) algorithm incorporating B&B and column generation is developed. Specifically, a new dynamic programming algorithm with new label structure and dominance rules is established to solve the pricing problem in B&P, and a new multi-layer branching scheme is developed for implementing the algorithm. The effectiveness and robustness of the proposed methodology are then tested on a set of randomly generated problems.
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\nThe second scenario extends the first by including transshipment activities in the ECRSVR (denoted as ECRSVRTS). Apparently, the inclusion of transshipment activities will significantly increase the size of the solution space of feasible routing and distribution schemes. Also, more constraints have to be included in the model to account for the interdependence between the distribution schemes of separate vessels. To tackle this problem, two mathematical models are developed. The first is a port-based model that explicitly characterizes the routing plans and distribution volumes for each vessel at each time interval as decision variables. The resulting integer program is non-linear and difficult to solve. Therefore, an equivalent event-driven node-based model inspired by the formulation of PDPTW is constructed. In this model, the pickup/delivery tasks and transshipment events are represented as nodes in a generated topology. The B&P scheme is then modified to solve the node-based model and a Hybrid Scatter Tabu Search (HSTS) is developed to solve the pricing problems. Results obtained from the numerical experiments using randomly generated test problems show that the proposed HSTS algorithm outperforms conventional scatter search and tabu search algorithms.

We address a logistics districting problem faced by a parcel company whose operations consist of picking up and delivering packages over a service region. The districting process aims to find a partition of the service region into delivery and collection zones that may be served by a single vehicle that departs from a central depot. Criteria to be optimized are to balance workload content among the districts and to create districts of compact shape. A solution approach based on a hybrid procedure that combines elements of GRASP and Tabu Search (TS) is proposed to solve large‐scale instances. Numerical experimentation is performed considering different instance sizes and types. Results show that the proposed solution approach is able to solve large‐scale instances in reasonable computational times with good quality of the solutions obtained. To determine the quality of the solutions, results are compared with CPLEX solutions and with the current real solution to highlight the benefits of the proposed approach. Conclusions and recommendations for further research are provided.

Since it was found in December 2019, the novel Coronavirus Disease 2019 (COVID-19) has spread from Wuhan, China, to many other countries. A rapid increase of newly found cases was observed, and finally, in March 2020, the World Health Organization declared that Coronavirus Disease 2019 (COVID-19) is a global pandemic. As one of the vulnerable groups, pregnant women need to avoid COVID-19 transmission and maintain pregnancy health during the pandemic. This study aimed to improve pregnant women's self-management during the COVID-19 pandemic in the working area of the Padangsari Primary Health Care Services, Semarang City. The research method used an experimental design with a pre-posttest without a control group. A Smartphone application, namely "SEHARI," was used to share the module and video about pregnancy health guidelines; furthermore, various activities of this study included online classes for pregnant women via a WhatsApp group, pregnancy care behavior surveys, and evaluations. The offline activity was done in 1 meeting for 90-120 minutes, while online activities were done as needed. This study's target population was 22 pregnant women in Puskesmas Padangsari Semarang City's working area selected by purposive sampling. A questionnaire was used that measures mother's behavior while engaging in pregnancy care and pregnancy examination screening. The validity and reliability tests showed that the instrument was valid and reliable to improve self-management of pregnant women during the COVID-19 pandemic in the working area. Bivariate data analysis of the independent variable's effect on the dependent variables used paired and independent t-tests to measure the self-management of pregnant women. The results showed that 50% of pregnant women fulfilled nutritional needs well, 59.1% of pregnant women did tetanus immunization, and 59.1% did pregnancy examinations and visits. Despite being a vulnerable group, pregnant women must continue their antenatal care during the pandemic with a strict health protocol. Specially designed online classes and Smartphone application can be used as media to deliver the essential health meassages so that pregnant women can still monitor their pregnancy health and have a way to bridge the existing programs in primary health care.

This paper has as objective to use the methodology “Lean Manufacturing”, to increase the productivity in the area of External Logistics and Delivery Services of the company Urbano Express, it was considered for the analysis to two fundamental processes of the area: (“Clearing Banking” that it contemplates the banks, insurers and internal messaging of financial entities and the “Domicile Service” that contemplates the food and medicine companies). With the lifting of the variables and the main factors that intervene in the processes, several tools were analyzed to generate an increase in productivity in the processes to be worked, in order to obtain an improvement in the profitability of the company and the area of research, the “5S” was implemented with the help of standardization and optimization in time and workload of the staff. We worked hand in hand with those responsible for each process and as a counterpart to the clients that intervene in this process, work areas were modified, the optimal time of each activity was determined with the use of a stopwatch, based on the obtained documentation generated the flow charts and diagrams of each process were carried out.

A stabilized branch-and-price-and-cut algorithm for the multiple length cutting stock problem

A mathematical formulation and a tabu search heuristic for the joint vessel-UAV routing problem

This paper conducted a research on the vehicle routing problem (VRP) for small–medium enterprise (SMEs) considering new and old shippers. The problem is motivated by a real-world scenario found between Changzhou’s small or medium enterprises (Shippers) and transportation companies (Carriers). Since the service time is different for new and old shippers in the real world, we obtained a set of rich VRP considering time windows and the working time of the vehicle, as well as distinguishing between old and new shippers. We also propose a hybrid algorithm that consists of ant colony optimization (ACO) and tabu search (TS). Carrier’s trade-off point of orders’ number is calculated by the hybrid algorithm. Meanwhile, scenarios of deterministic versus stochastic shippers’ demand and collaborative versus non-collaborative carriers are optimized by the algorithm. The results show that the collaborative transportation planning could improve the profits of carriers.

This paper studies a robust variant of the team orienteering problem with decreasing profits, where a fleet of vehicles are dispatched to serve customers with decreasing profits in a limited time horizon. The service times at customers are assumed to be uncertain, which are characterized by a budgeted uncertainty set. Our goal is to determine the set of customers to be served and the routes for the vehicles such that the collected profit is maximized; meanwhile, all the planned routes remain feasible for any realization of service times within the uncertainty set. We propose a two-index robust formulation for the problem, which is defined using constraints based on dynamic programming recursive equations and can be directly solved by a general-purpose optimization solver. We also present a route-based formulation for the problem, which is solved by a tailored branch-and-price (B&P) algorithm. To tackle large-size instances efficiently, we further implement a tabu search (TS) algorithm. Numerical tests show that our B&P algorithm can solve most instances with 100 customers to optimality within 30 minutes and that the TS algorithm can find high-quality solutions within a few seconds. Moreover, we find that in most cases, the robust solutions can significantly reduce the probability of deadline violations in simulation tests with only a slight compromise of profit compared with the solutions generated by the deterministic model. History: Accepted by Andrea Lodi, Area Editor for Design & Analysis of Algorithms—Discrete. Funding: This work was supported by the National Natural Science Foundation of China [Grants 72201267, 72101049, 72122015, 71971154] and the Fundamental Research Funds for the Central Universities, Civil Aviation University of China [Grant 3122022093]. Supplemental Material: The online supplement is available at https://doi.org/10.1287/ijoc.2022.1240 .

The entire project addresses the issue of mitigating additional intermittency and fast ramps that occur at higher penetration of intermittent resources, including wind genera-tion, in the Bonneville Power Administration (BPA) and the California Independent Sys-tem Operator (California ISO) control areas. The proposed Wide Area Energy Storage and Management System (WAEMS) will address the additional regulation requirement through the energy exchange between the participating control areas and through the use of energy storage and other generation resources. For the BPA and California ISO control centers, the new regulation service will look no different comparing with the traditional regulation resources. The proposed project will benefit the regulation service in these service areas, regardless of the actual degree of penetration of the intermittent resources in the regions. The project develops principles, algorithms, market integration rules, functional de-sign and technical specifications for the WAEMS system. The project is sponsored by BPA and supported in kind by California ISO, Beacon Power Corporation, and the Cali-fornia Energy Commission (CEC).