scholarly journals Evaluation of a facility location for a food assistance supply chain. The case of Bienestarina in Colombia

2020 ◽  
Vol 39 (3) ◽  
pp. 50-61
Author(s):  
Feizar Javier Rueda-Velasco ◽  
Wilson Adarme-Jaimes ◽  
Angélica Garzón-Luna ◽  
Jhonatan Marroquín-Ávila ◽  
Gabriel Parada-Caro
Keyword(s):  
Supply Chain ◽  
Facility Location ◽  
Programming Model ◽  
Food Assistance ◽  
Social Program ◽  
Policy Implications ◽  
Mixed Integer ◽  
Current Configuration ◽  
Location Allocation ◽  
The Government

The evaluation of the strategic supply chain configuration is considered one of the strategic logistics decisions, especially in food assistance supply chains focused on generating better nutritional conditions in vulnerable populations. In Colombia, there is a social program called Bienestarina, which aims to promote food and nutritional security in a vulnerable population. Although the government supports the program for improving nutritional support, there are currently inconsistencies in freight flows, lack of coverage in some areas, and delivery delays. Therefore, this work aims to evaluate the current configuration of the supply chain and propose improvements related to the facility location. Such advances would enable the increase in the efficacy of the network and the reduction of malnutrition in the country. For this purpose, a mixed-integer mathematical programming model is presented, which considers the weighted distance criterion for different demand scenarios and supports the location-allocation decision in a social assistance supply chain. The current network configuration was compared with the optimal proposed structure. The comparisons show highly potential improvements in freight flow allocation, suggests several variations in the existing warehouses emplacement, and generates public policy implications to reduce the logistic cost in the system, prioritizing in turn the demand covering.

scholarly journals The Nutritious Supply Chain: Optimizing Humanitarian Food Assistance

2021 ◽  
pp. ijoo.2019.0047
Author(s):  
Koen Peters ◽  
Sérgio Silva ◽  
Rui Gonçalves ◽  
Mirjana Kavelj ◽  
Hein Fleuren ◽  
...  
Keyword(s):  
Supply Chain ◽  
Programming Model ◽  
Food Assistance ◽  
Decision Makers ◽  
Mixed Integer ◽  
Sourcing Strategies ◽  
Humanitarian Agency ◽  
Operational Excellence ◽  
Functional Areas

The World Food Programme (WFP) is the largest humanitarian agency fighting hunger worldwide, reaching approximately 90 million people with food assistance across 80 countries each year. To deal with the operational complexities inherent in its mandate, WFP has been developing tools to assist its decision makers with integrating supply chain decisions across departments and functional areas. This paper describes a mixed integer linear programming model that simultaneously optimizes the food basket to be delivered, the sourcing plan, the delivery plan, and the transfer modality of a long-term recovery operation for each month in a predefined time horizon. By connecting traditional supply chain elements to nutritional objectives, we are able to make significant breakthroughs in the operational excellence of WFP’s most complex operations. We show three examples of how the optimization model is used to support operations: (1) to reduce the operational costs in Iraq by 12% without compromising the nutritional value supplied, (2) to manage the scaling-up of the Yemen operation from three to six million beneficiaries, and (3) to identify sourcing strategies during the El Niño drought of 2016.

scholarly journals Minimising negative externalities cost using 0-1 mixed integer linear programming model in e-commerce environment

2017 ◽  
Vol 11 ◽  
Author(s):  
Akyene Tetteh ◽  
Sarah Dsane-Nsor
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Petroleum Products ◽  
Mixed Integer ◽  
The Internet ◽  
Negative Externalities ◽  
The Government ◽  
The Cost

Background: Although the Internet boosts business profitability, without certain activities like efficient transportation, scheduling, products ordered via the Internet may reach their destination very late. The environmental problems (vehicle part disposal, carbon monoxide [CO], nitrogen oxide [NOx] and hydrocarbons [HC]) associated with transportation are mostly not accounted for by industries.Objectives: The main objective of this article is to minimising negative externalities cost in e-commerce environments.Method: The 0-1 mixed integer linear programming (0-1 MILP) model was used to model the problem statement. The result was further analysed using the externality percentage impact factor (EPIF).Results: The simulation results suggest that (1) The mode of ordering refined petroleum products does not impact on the cost of distribution, (2) an increase in private cost is directly proportional to the externality cost, (3) externality cost is largely controlled by the government and number of vehicles used in the distribution and this is in no way influenced by the mode of request (i.e. Internet or otherwise) and (4) externality cost may be reduce by using more ecofriendly fuel system.

scholarly journals Local Blood Supply Chain Optimization: A Case Study

2020 ◽  
Vol 18 (4) ◽  
Author(s):  
Reza Babazadeh ◽  
Ali Sabbaghnia ◽  
Fatemeh Shafipour
Keyword(s):  
Supply Chain ◽  
Blood Supply ◽  
Blood Donation ◽  
Programming Model ◽  
Human Life ◽  
Mixed Integer ◽  
Model Parameters ◽  
Supply Chain Optimization ◽  
Blood Supply Chain ◽  
Proposed Model

: Blood and its products play an undeniable role in human life. In recent years, although both academics and practitioners have investigated blood-related problems, further enhancement is still warranted. In this study, a mixed-integer linear programming model was proposed for local blood supply chain management. A supply network, including temporary and fixed blood donation facilities, blood banks, and blood processing centers, was designed regarding the deteriorating nature of blood. The proposed model was applied in a real case in Urmia, Iran. The numerical results and sensitivity analysis of the key model parameters ensured the applicability of the proposed model.

Methodology for the Design of Traceability System in Food Assistance Supply Chains

2021 ◽  
pp. 440-461
Author(s):  
Feizar Javier Rueda-Velasco ◽  
Angie Monsalve-Salamanca ◽  
Wilson Adarme-Jaimes
Keyword(s):  
Public Policy ◽  
Supply Chain ◽  
Quantitative Comparison ◽  
Social Conditions ◽  
Food Assistance ◽  
Policy Implications ◽  
Technological Infrastructure ◽  
Traceability System ◽  
The Social ◽  
New Criteria

The food assistance programmes (FAP) has the mission to guarantee minimum nutrition requirements in a vulnerable population. Nevertheless, the small deliveries for a spread population, the social conditions, and the limited technological infrastructure could make it difficult to adequately aid supply. To solve these limitations, this chapter proposes a methodology for the design of traceability systems in FAP which allows increasing supply chain visibility, coordination between deliveries and social conditions, and therefore, possible impacts on public policy implications. A qualitative and quantitative comparison of the conventional frameworks is carried out and contrast with the needs of the programmes studied. Also, new criteria are also added to adapt the design to the technological infrastructure and the socio-demographic conditions of the territory. The methodological proposal is applied to the Bienestarina nutritional programme in Colombia, where the technologies and tools to subsequently design the traceability system are proposed.

scholarly journals Optimal Design of Bioenergy Supply Chains Considering Social Benefits: A Case Study in Northeast China

Processes ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 437 ◽  
Author(s):  
Cong Gao ◽  
Daogang Qu ◽  
Yang Yang
Keyword(s):  
Supply Chain ◽  
Optimal Design ◽  
Supply Chains ◽  
Northeast China ◽  
Liaoning Province ◽  
Mixed Integer ◽  
Social Benefits ◽  
Economic Activities ◽  
The Social ◽  
The Government

Bioenergy supply chains can offer social benefits. In most related research, the total number of created jobs is used as the indicator of social benefits. Only a few of them quantify social benefits considering the different impact of economic activities in different locations. In this paper, a new method of measuring the social benefits of bioethanol supply chains is proposed that considers job creation, biomass purchase, and the different impacts of economic activities in different locations. A multi-objective mixed integer linear programming (MILP) model is developed to address the optimal design of a bioethanol supply chain that maximizes both economic and social benefits. The ε-constraint method is employed to solve the model and a set of Pareto-optimal solutions is obtained that shows the relationship between the two objectives. The developed model is applied to case studies in Liaoning Province in Northeast China. Actual data are collected as practical as possible for the feasibility and effectiveness of the results. The results show that the bioethanol supply chain can bring about both economic and social benefits in the given area and offers governments a better and more efficient way to create social benefits. The effect of the government subsidy on enterprises’ decisions about economic and social benefits is discussed.

scholarly journals Supply chain optimization with variable demand by considering financial criteria and scenarios

2017 ◽  
Vol 26 (44) ◽  
pp. 21 ◽  
Author(s):  
John Willmer Escobar
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Net Present Value ◽  
Programming Model ◽  
Supply Chain Design ◽  
Mixed Integer ◽  
Supply Network ◽  
Distribution Centers ◽  
Supply Chain Optimization ◽  
Starting Point

This paper contemplates the supply chain design problem of a large-scale company by considering the maximization of the Net Present Value. In particular, the variability of the demand for each type of product at each customer zone has been estimated. As starting point, this paper considers an established supply chain for which the main problem is to determine the decisions regarding expansion of distribution centers. The problem is solved by using a mixed-integer linear programming model, which optimizes the different demand scenarios. The proposed methodology uses a scheme of optimization based on the generation of multiple demand scenarios of the supply network. The model is based on a real case taken from a multinational food company, which supplies to the Colombian and some international markets. The obtained results were compared with the equivalent present costs minimization scheme of the supply network, and showed the importance and efficiency of the proposed approach as an alternative for the supply chain design with stochastic parameters.

scholarly journals A Nonlinear Integer Programming Model for Integrated Location, Inventory, and Routing Decisions in a Closed-Loop Supply Chain

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Hao Guo ◽  
Congdong Li ◽  
Ying Zhang ◽  
Chunnan Zhang ◽  
Yu Wang
Keyword(s):  
Supply Chain ◽  
Integer Programming ◽  
Facility Location ◽  
Vehicle Routing ◽  
Closed Loop ◽  
Programming Model ◽  
Nonlinear Integer Programming ◽  
Inventory Routing ◽  
Closed Loop Supply Chain ◽  
Integer Programming Model

Facility location, inventory management, and vehicle routing are three important decisions in supply chain management, and location-inventory-routing problems consider them jointly to improve the performance and efficiency of today’s supply chain networks. In this paper, we study a location-inventory-routing problem to minimize the total cost in a closed-loop supply chain that has forward and reverse logistics flows. First, we formulate this problem as a nonlinear integer programming model to optimize facility location, inventory control, and vehicle routing decisions simultaneously in such a system. Second, we develop a novel heuristic approach that incorporates simulated annealing into adaptive genetic algorithm to solve the model efficiently. Last, numerical analysis is presented to validate our solution approach, and it also provides meaningful managerial insight into how to improve the closed-loop supply chain under study.

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