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This chapter describes and discusses the main results of the successful off-hour delivery (OHD) pilot test in the city of São Paulo, Brazil, which took place between October 2014 and March 2015. The pilot engaged major stakeholders in urban distribution, including local authorities, shippers, carriers, and receivers, with the aim to determine what are the main requirements, constraints, opportunities, and threats for establishing a public policy related to shifting deliveries to late night in order to mitigate traffic congestion.

Differently from the former City of New York OHD pilot, here all participant companies were volunteers, with no need for cash incentives. The primary focus in São Paulo was on the issues of safety and noise, besides productivity aspects of travel time, truck speed, and delivery time.

The pilot was very successful, with no registered complaints of noise or security incidents. Travel speeds were obtained from global positioning system (GPS) tracking data and internal delivery systems. The chapter compares daytime and night operations and shows that productivity in some chains would improve significantly, but noise and safety must be carefully controlled to guarantee the expansion of the concept.

This paper aims to present the internalization process by which Venezuelan migrants and refugees are resettled. Using system dynamics, the authors model a Brazilian humanitarian operation (“Acolhida” – Welcome), simulate the internalization process, propose policies and provide lessons learned for future migratory operations.

Using system dynamics simulation, the authors use Acolhida Operation’s historical data to recreate the reception and resettlement process of Venezuelan migrants and refugees. The authors identify the main bottlenecks in the system and propose policies to respond to scenarios according to the number of internalization vacancies, that is, available places in Brazil where migrants and refugees can be resettled. Finally, based on interviews with former decision-makers, the model represents a first attempt to convert the pressure of public opinion on authorities into temporary shelters as a way of reducing the number of unassisted people.

The results confirm that internalization vacancies are the main constraint when resettling Venezuelan migrants and refugees. Had the internalization program been promoted since the operation’s beginning, there would have been fewer unassisted people in Roraima and fewer shelters. The pressure-converting mechanism presented in this study, although incipient, constitutes a first attempt to support decision-makers in determining when to build temporary shelters.

This study can be useful to public authorities and humanitarian organizations when developing policies to enhance resettlement in migratory crises. In Acolhida’s case, the internalization program should continue to be the operation’s priority and can be enhanced by investing more resources to create internalization vacancies while maintaining logistical capacities.

The authors suggest policies to improve the Acolhida internalization program: give more people the choice to relocate in other cities, increase turnover in shelters and provide a more efficient and effective response to Venezuelan migration in Roraima.

Although a number of studies have applied system dynamics to humanitarian operations, few models have focused on migratory emergencies, such as those occurring in northern Brazil. The model is applied to the largest humanitarian operation carried out in the Brazilian territory and provides decision-makers with valuable insights and alternatives for better implementation in the future. Furthermore, this study narrows the gap between the social sciences and modeling and simulation techniques by proposing ways of predicting migratory implications in the construction of shelters and resettlement policies.

The fast growth of urban areas in major cities worldwide is undoubtedly one of the biggest concerns for city officials. In Latin America, data show that currently 81% of its inhabitants live in urban areas, and calculations forecast an increase in this percentage. In this context, urban logistics would become increasingly important in the overall performance of the region and its cities. The main objective of this study was to develop a set of key performance indicators (KPIs) to complement the square kilometer (km²) methodology developed by MIT, applying it in a highly intensive HORECA (hotels, restaurant, coffee shops) area known as “Zona T (The T Zone)” in Bogotá, Colombia, as this is a critical area where distribution needs to be performed at its best. Data such as shop inventory (stores, restaurants, drugstores, etc.), vehicle counting (cars, buses, motorbikes, trucks, etc.), product deliveries (by type: perishables, groceries, cleaning supplies, etc.), and traffic disruptions were collected through observation. Based on literature review and results of the study, 13 KPIs are proposed in three categories: operational (average distance and store coverage, service time & service rate, store density, delivery points, easiness for delivery and vehicle delivery factor), energy and environmental (fuel consumption and emissions), and traffic (traffic density, speed and traffic per lane). The main results show a 62-m average distance from truck to store, service time of 18:36 min, 1.019 gal and 9.1 kg CO₂e of fuel consumption and emission, respectively, traffic density of 421 vehicles/h, and other results described throughout the document.

The objective of inventory management models is to determine efficient policies for managing the trade-off between customer satisfaction and the cost of goods. This chapter presents a methodology that uses the Monte Carlo Method (MCM) to estimate the behavior of a raw material supply model, considering uncertain variables such as demand, prices, and exchange rates. In order to show how to use this methodology, we analyze the case of a Colombian company in the aluminum industry. This company imports aluminum sheets from China. In this case, we analyze the financial impact of the raw material supply contract proposed by the Chinese supplier. The model considers different supply scenarios for the raw material. We calculate robust indicators such as Value at Risk (VaR), the Conditional Value at Risk (CVaR) and the probability of success for each scenario analyzed. Finally, we conduct a sensitivity analysis with respect to the sales price to validate the proposed models and solution approaches. The results show that considering risk metrics to evaluate the impact of endogenous factors over the supply process is a useful approach to improve decision-making related to this process and also can help to ensure the profitability of the company.

Waste production is one of the most important problems that humankind faces. Human-based activities generate diverse waste types that have to be treated and disposed differently. This results in the need to build more facilities to manage the waste and to avoid further environmental damage. Colombia established a successful policy to close open dumps and to control pollution. Notwithstanding the advances that have been made in final disposal, it is necessary to extend the life of the final disposal sites and increase the closure of open landfills. Valle del Cauca is the third most populated Colombian province, and it is also considered the third province that generates more waste. This chapter addresses the problem of locating solid waste disposal centers in Valle del Cauca by applying the analytic hierarchy process (AHP) with fuzzy logic, a multicriteria method that compares opinions of a decision-making group. Additionally, each potential location area is characterized by considering industrial and environmental issues, societal dynamics, infrastructure and topography, costs, and taxes. After applying a variant of AHP, the decision-making group was able to find that Jamundi is the best location to open the disposal center. The method shows strong potential to identify and prioritize alternative locations for a diverse group of stakeholders. Most importantly, the methodology lets us structure better qualitative and quantitative data, as well as to link multiple levels to avoid choosing locations that will affect society, environment, and other stakeholders, without considering the trade-offs among diverse criteria considering benefits, opportunities, costs, and risks (BOCR).

This note explores the applicability of evaluation criteria to the problem of evaluating the supply chain strategy (SCS) of an organization. A discussion of SCS evaluation is relevant today, as the validity of the dominant approach – proposed two decades ago and based on matching types – has come into question. While evaluation criteria have a long history in other disciplines, they are new to SCS evaluation. To help supply chain (SC) scholars assess the applicability of evaluation criteria to SCS, this note proposes a tentative set of criteria and provides insights derived from the authors’ recent experience. We propose that the use of criteria for the evaluation of SCS may be a useful alternative, or at least a complement, to the dominant approach. These proposed criteria are currently being validated in a project with a company in Uruguay; we invite further empirical validation by third parties.

Since the sixteenth century, Panama has been an important logistic node for communication between South America, North America, and Europe for trade and load transit. Panama ports move more than 700 million tons per year while Panama Canal moves 325,428,407 tons, according the statistics of 2014. Most of the maritime cargo moved through Panama is transit and transshipment cargo. Consequently, and due to the geographical position and future opportunities based on the expansion of the Panama Canal, Panama could be a strategic hub of global trade flows. This is an opportunity to develop value-added logistics services (VALS) in Panama Canal. Thus, this research aims to present a preliminary analysis of VALS industry in Panama, identifying critical variables that could enhance these services. This is a survey-based research, using interviews with the main suppliers of VALS in Panama and some of their customers. The methodology applied to analyze the data is means-end value hierarchy model (MEVHM), which was used to understand VALS industry in Panama and identify what is valuable to customers. Results showed that each VALS provider serves a mean of 20 companies, 22% of them are national clients while 78% are international clients, which recognized the geographical position as their main reason to work with logistics experts from Panama. Furthermore, 92% of them were very satisfied or satisfied with the service received. Main VALS in Panama are labeling, tagging, and packaging. In contrast, areas to be improved are customs procedures, national logistics processes, product’s traceability, competitive prices, and human resources training.

This chapter proposes a hybrid heuristic method combining a clustering search (CS) metaheuristic with an exact algorithm to solve a two-stage capacitated facility location problem (TSCFLP). The TSCFLP consists of defining the optimal locations of plants and depots and the product flow from plants to depots (first stage) and from depots to customers (second stage). The problem deals commonly with cargo transportation in which products must be transported from a set of plants to meet customers’ demands passing out by intermediate depots. The main decisions to be made are related to define which plants and depots must be opened from a given set of potential locations, which customer to assign to each one of the opened depots, and the amount of product flow from the plants to the depots and from the depots to the customers. The objective is to minimize costs satisfying demand and capacity constraints. Computational results demonstrate that our method was able to find good solutions when comparing it directly with a commercial solver and a genetic algorithm (GA) reported in a recent chapter found in the literature, requiring less than 1.5% and 41% of the computational time performed by these methods, respectively. Thus, our hybrid method combining CS with an exact algorithm can be considered as a new matheuristic to solve the TSCFLP.