scholarly journals A Simulated Annealing Methodology to Multiproduct Capacitated Facility Location with Stochastic Demand

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jin Qin ◽  
Hui Xiang ◽  
Yong Ye ◽  
Linglin Ni
Keyword(s):  
Simulated Annealing ◽  
Facility Location ◽  
Programming Model ◽  
Transportation Cost ◽  
Mixed Integer ◽  
Optimal Decision ◽  
Location Decision ◽  
Inventory Cost ◽  
Stochastic Demands ◽  
Capacitated Facility Location

A stochastic multiproduct capacitated facility location problem involving a single supplier and multiple customers is investigated. Due to the stochastic demands, a reasonable amount of safety stock must be kept in the facilities to achieve suitable service levels, which results in increased inventory cost. Based on the assumption of normal distributed for all the stochastic demands, a nonlinear mixed-integer programming model is proposed, whose objective is to minimize the total cost, including transportation cost, inventory cost, operation cost, and setup cost. A combined simulated annealing (CSA) algorithm is presented to solve the model, in which the outer layer subalgorithm optimizes the facility location decision and the inner layer subalgorithm optimizes the demand allocation based on the determined facility location decision. The results obtained with this approach shown that the CSA is a robust and practical approach for solving a multiple product problem, which generates the suboptimal facility location decision and inventory policies. Meanwhile, we also found that the transportation cost and the demand deviation have the strongest influence on the optimal decision compared to the others.

Insights to optimise marketing decisions on pig-grower farms

2019 ◽  
Vol 59 (6) ◽  
pp. 1126 ◽  
Author(s):  
S. V. Rodríguez-Sanchez ◽  
L. M. Pla-Aragones ◽  
R. De Castro
Keyword(s):  
Weight Control ◽  
Time Window ◽  
Programming Model ◽  
Transportation Cost ◽  
Management Policy ◽  
Mixed Integer ◽  
Factors Affecting ◽  
Pig Production ◽  
Marketing Policy ◽  
Feeding Program

Modern pig production in a vertically integrated company is a highly specialised and industrialised activity, requiring increasingly complex and critical decision-making. The present paper focuses on the decisions made on the pig-grower farms operating on an all-in–all-out management policy at the last stage of pig production. Based on a mixed-integer linear-programming model, an assessment for specific parameters to support marketing decisions on farms without individual weight control is made. The analysis of several key factors affecting the optimal marketing policy, such as transportation cost, when and how many pigs to deliver to the abattoir and weight homogeneity of the batch, served to gain insight into marketing decisions. The results confirmed that not just the feeding program, but also the grading price system, transportation and batch homogeneity have an enormous impact on the optimal marketing policy of fattening farms in a vertically integrated company. In addition, within the range of conditions considered, a time window of 4 weeks was deemed as optimal for delivering animals to the abattoir and the subsequent revenue was 15% higher than with traditional marketing rules.

scholarly journals A Synchronous Optimization Model for Multiship Shuttle Tanker Fleet Design and Scheduling Considering Hard Time Window Constraint

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Zhenfeng Jiang ◽  
Dongxu Chen ◽  
Zhongzhen Yang
Keyword(s):  
Time Window ◽  
Programming Model ◽  
Transportation Cost ◽  
Exact Algorithm ◽  
Mixed Integer ◽  
Routing Problem ◽  
Hard Time ◽  
Proposed Model ◽  
Total Transportation Cost ◽  
Time Window Constraints

A Synchronous Optimization for Multiship Shuttle Tanker Fleet Design and Scheduling is solved in the context of development of floating production storage and offloading device (FPSO). In this paper, the shuttle tanker fleet scheduling problem is considered as a vehicle routing problem with hard time window constraints. A mixed integer programming model aiming at minimizing total transportation cost is proposed to model this problem. To solve this model, we propose an exact algorithm based on the column generation and perform numerical experiments. The experiment results show that the proposed model and algorithm can effectively solve the problem.

Lagrangian Bounds and a Heuristic for the Two-Stage Capacitated Facility Location Problem

2012 ◽  
Vol 1 (1) ◽  
pp. 59-71 ◽  
Author(s):  
Igor Litvinchev ◽  
Edith L. Ozuna
Keyword(s):  
Facility Location ◽  
Location Problem ◽  
Computational Study ◽  
Facility Location Problem ◽  
Mixed Integer ◽  
Variable Cost ◽  
Fixed Cost ◽  
Two Stage ◽  
Capacitated Facility Location Problem ◽  
Capacitated Facility Location

In the two-stage capacitated facility location problem, a single product is produced at some plants in order to satisfy customer demands. The product is transported from these plants to some depots and then to the customers. The capacities of the plants and depots are limited. The aim is to select cost minimizing locations from a set of potential plants and depots. This cost includes fixed cost associated with opening plants and depots, and variable cost associated with both transportation stages. In this work, two different mixed integer linear programming formulations are considered for the problem. Several Lagrangian relaxations are analyzed and compared, and a Lagrangian heuristic producing feasible solutions is presented. The results of a computational study are reported.

scholarly journals Congestion Service Facilities Location Problem with Promise of Response Time

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Dandan Hu ◽  
Zhi-Wei Liu ◽  
Wenshan Hu
Keyword(s):  
Response Time ◽  
Location Problem ◽  
Service Providers ◽  
Programming Model ◽  
Mixed Integer ◽  
Specific Response ◽  
Location Decision ◽  
Decision Variables ◽  
Facilities Location ◽  
Nonlinear Programming Model

In many services, promise of specific response time is advertised as a commitment by the service providers for the customer satisfaction. Congestion on service facilities could delay the delivery of the services and hurts the overall satisfaction. In this paper, congestion service facilities location problem with promise of response time is studied, and a mixed integer nonlinear programming model is presented with budget constrained. The facilities are modeled as M/M/c queues. The decision variables of the model are the locations of the service facilities and the number of servers at each facility. The objective function is to maximize the demands served within specific response time promised by the service provider. To solve this problem, we propose an algorithm that combines greedy and genetic algorithms. In order to verify the proposed algorithm, a lot of computational experiments are tested. And the results demonstrate that response time has a significant impact on location decision.

scholarly journals Five-Echelon Multiobjective Health Services Supply Chain Modeling under Disruption

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Farnaz Javadi Gargari ◽  
Mahjoube Sayad ◽  
Seyed Ali Posht Mashhadi ◽  
Abdolhossein Sadrnia ◽  
Arman Nedjati ◽  
...  
Keyword(s):  
Supply Chain ◽  
Optimization Model ◽  
Optimization Problem ◽  
Programming Model ◽  
Transportation Cost ◽  
Real Data ◽  
Mixed Integer ◽  
Fixed Cost ◽  
Hub Location ◽  
Goal Programming Model

Medicine unreliability problem is taken into consideration as one of the most important issues in health supply chain management. This research is associated with the development of a multiobjective optimization problem for the selection of suppliers and distributors. To achieve the purposes, the optimal quota allocation is determined with respect to disruption of suppliers in a five-echelon supply chain network and consideration of the distributor centers as a hub location-allocation mode. The objective of the optimization model is involved in simultaneous minimization of transactions costs dealing with suppliers, expected purchasing costs from suppliers, expected percentages of delayed and returned products in each distributor, as well as transportation cost in each echelon and fixed cost for distributor centers, and finally maximization of the expected scores for suppliers and high priority of product customers. The optimization problem is formulated as a mixed-integer nonlinear programming model. The proposed optimization model is utilized to investigate a numerical case study for asthma-specific medicines. The analyzing procedure is conducted based on the collected real data from Cobel Darou pharmaceutical company in 2019. Furthermore, a fuzzy multichoice goal programming model is considered to solve the proposed optimization model by R optimization solver. The numerical results confirmed the authenticity of the model.

scholarly journals Combined Simulated Annealing Algorithm for the Discrete Facility Location Problem

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Jin Qin ◽  
Ling-lin Ni ◽  
Feng Shi
Keyword(s):  
Simulated Annealing ◽  
Facility Location ◽  
Location Problem ◽  
Simulated Annealing Algorithm ◽  
Facility Location Problem ◽  
Location Decision ◽  
Previous Algorithm ◽  
Annealing Algorithm ◽  
Discrete Facility Location ◽  
Better Than

The combined simulated annealing (CSA) algorithm was developed for the discrete facility location problem (DFLP) in the paper. The method is a two-layer algorithm, in which the external subalgorithm optimizes the decision of the facility location decision while the internal subalgorithm optimizes the decision of the allocation of customer's demand under the determined location decision. The performance of the CSA is tested by 30 instances with different sizes. The computational results show that CSA works much better than the previous algorithm on DFLP and offers a new reasonable alternative solution method to it.

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.

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