scholarly journals Coordinating the Supply Chain Network and Optimization Models of Agricultural Products in Bangladesh

2020 ◽  
pp. 57-72
Author(s):  
Mohammad Khairul Islam ◽  
Md. Mahmud Alam ◽  
Mohammed Forhad Uddin
Keyword(s):  
Supply Chain ◽  
Agricultural Products ◽  
Mixed Integer ◽  
Optimization Models ◽  
Supply Chain Network ◽  
User Cost ◽  
External Sources ◽  
Business Contract ◽  
Milp Model ◽  
The Individual

In this research introduces four different mathematical designs for the coordination and three-stage profit optimization models of agricultural products in Bangladesh. This research, we occupied that the three types of market players are coordinated by mutually sharing all kind of information related to their business. To enrich a Mixed Integer Linear Programming (MILP) model and explore the circumstance of production receptivity is inadequate for the manufacturer. The manufacturers will coverage these deficits by external sources, which decided very beginning of the business contract. This is very significant foreword in deciding so as to alleviate these challenges and to enlarge the method representation and distinct benefit of the Supply Chain Network (SCN). The coordinated system in alliance with the market players has been projected to realize the best result. The formulated MILP models optimize the maximum profit and also to optimize the best production distribution center which satisfy most of the customer demand. This paper, the formulated MILP model were solved by a mathematical programming language (AMPL) and we get the results by using appropriate solver MINOS. Analyzed a numerical example for some important parameters has been deployed to validate our proposed models. We get the results after coordination the individual profits could be increased, in the same time end user cost price decrease.

Closed supply network modelling for end-of-life ship remanufacturing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Prem Chhetri ◽  
Mahsa Javan Nikkhah ◽  
Hamed Soleimani ◽  
Shahrooz Shahparvari ◽  
Ashkan Shamlou
Keyword(s):  
Supply Chain ◽  
End Of Life ◽  
Closed Loop ◽  
Payback Period ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Supply Network ◽  
Closed Loop Supply Chain ◽  
Content Type ◽  
Milp Model

PurposeThis paper designs an optimal closed-loop supply chain network with an integrated forward and reverse logistics to examine the possibility of remanufacturing end-of-life (EoL) ships.Design/methodology/approachExplanatory variables are used to estimate the number of EoL ships available in a closed-loop supply chain network. The estimated number of EoL ships is used as an input in the model and then it is solved by a mixed-integer linear programming (MILP) model of the closed-loop supply chain network to minimise the total logistic costs. A discounted payback period formula is developed to calculate the length of time to recoup an investment based on the investment's discounted cash flows. Existing ship wrecking industry clusters in the Western region of India are used as the case study to apply the proposed model.FindingsThe MILP model has optimised the total logistics costs of the closed-loop supply network and ascertained the optimal number and location of remanufacturing for building EoL ships. The capital and variable costs required for establishing and operating remanufacturing centres are computed. To remanufacture 30 ships a year, the discounted payback period of this project is estimated to be less than two years.Practical implicationsShip manufacturing businesses are yet to re-manufacture EoL ships, given high upfront capital expenditure and operational challenges. This study provides management insights into the costs and benefits of EoL ship remanufacturing; thus, informing the decision-makers to make strategic operational decisions.Originality/valueThe design of an optimal close loop supply chain network coupled with a Bayesian network approach and discounted payback period formula for the collection and remanufacturing of EoL ships provides a new integrated perspective to ship manufacturing.

scholarly journals A Multi-objective MILP Model Proposed to Optimize a Supply Chain Network for Microalgae-based Biofuels and Co-products: A Case Study in Iran

2021 ◽  
Author(s):  
Mohammad Ehsan Zerafati ◽  
Ali Bozorgi-Amiri ◽  
Amir-Mohammad Golmohammadi ◽  
Fariborz Jolai
Keyword(s):  
Supply Chain ◽  
Objective Function ◽  
Environmental Impacts ◽  
Deterministic Model ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Multi Objective ◽  
Proposed Model ◽  
Milp Model

Abstract Recently, due to the efficiency of cultivating microalgae, researchers and investors have paid considerable attention to the production of different biofuel products that are environmentally friendly. In this study, a two-stage deterministic model is proposed to design a microalgae-based biofuels and co-products supply chain network (MBCSCN). In the first stage, the appropriate locations for the cultivation of microalgae are identified through the analytical hierarchy process (AHP). In the second stage, a deterministic mathematical mixed integer linear programing (MILP) model is developed for a period of five years based on the criteria of economic and environmental impacts. The economic objective function maximizes the overall profit, while the environmental impacts objective function seeks to minimize the consumed fossil fuel throughout the supply chain. Then, a multi-objective MILP optimization problem is solved using the ε-constraint method. The proposed model is evaluated through a case study in Iran. It has helped to identify appropriate locations for the cultivation of microalgae and to specify the required quantity of feedstock, the species of microalgae, the required technology, and the transportation modes in each step of the supply chain.

scholarly journals A multi-objective approach under uncertainty for designing a green meat supply chain network

2021 ◽  
Author(s):  
Fatemeh Mohebalizadehgashti
Keyword(s):  
Linear Programming ◽  
Supply Chain ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Mixed Integer ◽  
Environmental Concerns ◽  
Supply Chain Network ◽  
Food Supply Chain ◽  
Multi Objective ◽  
Proposed Model

Traditional logistics management has not focused on environmental concerns when designing and optimizing food supply chain networks. However, the protection of the environment is one of the main factors that should be considered based on environmental protection regulations of countries. In this thesis, environmental concerns with a mathematical model are investigated to design and configure a multi-period, multi-product, multi-echelon green meat supply chain network. A multi-objective mixed-integer linear programming formulation is developed to optimize three objectives simultaneously: minimization of the total cost, minimization of the total CO2 emissions released from transportation, and maximization of the total capacity utilization. To demonstrate the efficiency of the proposed optimization model, a green meat supply chain network for Southern Ontario, Canada is designed. A solution approach based on augmented εε-constraint method is developed for solving the proposed model. As a result, a set of Pareto-optimal solutions is obtained. Finally, the impacts of uncertainty on the proposed model are investigated using several decision trees. Optimization of a food supply chain, particularly a meat supply chain, based on multiple objectives under uncertainty using decision trees is a new approach in the literature. Keywords: Meat supply chain; Decision tree; Multi-objective programming; Mixed-integer linear programming; Augmented εε-constraint.

A note on bi-objective optimization for sustainable supply chain network design in omnichannel

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Weidong Lei ◽  
Dandan Ke ◽  
Pengyu Yan ◽  
Jinsuo Zhang ◽  
Jinhang Li
Keyword(s):  
Mixed Integer ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Sustainable Supply Chain ◽  
Content Type ◽  
Product Flow ◽  
Flow Balance ◽  
Mip Model ◽  
Milp Model ◽  
Facility Capacity

PurposeThis paper aims to correct the existing mixed integer programming (MIP) model proposed by Yadav et al. (2019) [“Bi-objective optimization for sustainable supply chain network design in omnichannel.”, Journal of Manufacturing Technology Management, Vol. 30 No. 6, pp. 972–986].Design/methodology/approachThis paper first presents a counterexample to show that the existing MIP model is incorrect and then proposes an improved mixed integer linear programming (MILP) model for the considered problem. Last, a numerical experiment is conducted to test our improved MILP model.FindingsThis paper demonstrates that the formulations of the facility capacity constraints and the product flow balance constraints in the existing MIP model are incorrect and incomplete. Due to this reason, infeasible solutions could be identified as feasible ones by the existing MIP model. Hence, the optimal solution obtained with the existing MIP model could be infeasible. A counter-example is used to verify our observations. Computational results verify the effectiveness of our improved MILP model.Originality/valueThis paper gives a complete and correct formulation of the facility capacity constraints and the product flow balance constraints, and conducts other improvements on the existing MIP model. The improved MILP model can be easily implemented and would help companies to have more effective distribution networks under the omnichannel environment.

scholarly journals Determining nodal capacities for military distribution problems

2019 ◽  
Vol 3 (2) ◽  
pp. 110-130 ◽  
Author(s):  
Dave C. Longhorn ◽  
Joshua R. Muckensturm
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
The United States ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Multiple Time ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Content Type ◽  
Distribution Problems

Purpose This paper aims to introduce a new mixed integer programming formulation and associated heuristic algorithm to solve the Military Nodal Capacity Problem, which is a type of supply chain network design problem that involves determining the amount of capacity expansion required at theater nodes to ensure the on-time delivery of military cargo. Design/methodology/approach Supply chain network design, mixed integer programs, heuristics and regression are used in this paper. Findings This work helps analysts at the United States Transportation Command identify what levels of throughput capacities, such as daily processing rates of trucks and railcars, are needed at theater distribution nodes to meet warfighter cargo delivery requirements. Research limitations/implications This research assumes all problem data are deterministic, and so it does not capture the variations in cargo requirements, transit times or asset payloads. Practical implications This work gives military analysts and decision makers prescriptive details about nodal capacities needed to meet demands. Prior to this work, insights for this type of problem were generated using multiple time-consuming simulations often involving trial-and-error to explore the trade space. Originality/value This work merges research of supply chain network design with military theater distribution problems to prescribe the optimal, or near-optimal, throughput capacities at theater nodes. The capacity levels must meet delivery requirements while adhering to constraints on the proportion of cargo transported by mode and the expected payloads for assets.

scholarly journals Combined Use of Mathematical Optimization and Design of Experiments for the Maximization of Profit in a Four-Echelon Supply Chain

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-25 ◽  
Author(s):  
Daniel Arturo Olivares Vera ◽  
Elias Olivares-Benitez ◽  
Eleazar Puente Rivera ◽  
Mónica López-Campos ◽  
Pablo A. Miranda
Keyword(s):  
Supply Chain ◽  
Design Of Experiments ◽  
Mathematical Optimization ◽  
Fractional Factorial ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Cost Component ◽  
Allocation Model

This paper develops a location-allocation model to optimize a four-echelon supply chain network, addressing manufacturing and distribution centers location, supplier selection and flow allocation for raw materials from suppliers to manufacturers, and finished products for end customers, while searching for system profit maximization. A fractional-factorial design of experiments is performed to analyze the effects of capacity, quality, delivery time, and interest rate on profit and system performance. The model is formulated as a mixed-integer linear programming problem and solved by using well-known commercial software. The usage of factorial experiments combined with mathematical optimization is a novel approach to address supply chain network design problems. The application of the proposed model to a case study shows that this combination of techniques yields satisfying results in terms of both its behavior and the obtained managerial insights. An ANOVA analysis is executed to quantify the effects of each factor and their interactions. In the analyzed case study, the transportation cost is the most relevant cost component, and the most relevant opportunity for profit improvement is found in the factor of quality. The proposed combination of methods can be adapted to different problems and industries.

scholarly journals Designing a Supply Chain Network under the Risk of Disruptions

2012 ◽  
Vol 2012 ◽  
pp. 1-23 ◽  
Author(s):  
Armin Jabbarzadeh ◽  
Seyed Gholamreza Jalali Naini ◽  
Hamid Davoudpour ◽  
Nader Azad
Keyword(s):  
Supply Chain ◽  
Supply Chain Design ◽  
Mixed Integer ◽  
Nonlinear Program ◽  
Supply Chain Network ◽  
Large Problem ◽  
Solution Methods ◽  
Total Profit ◽  
Order Quantities ◽  
Problem Instances

This paper studies a supply chain design problem with the risk of disruptions at facilities. At any point of time, the facilities are subject to various types of disruptions caused by natural disasters, man-made defections, and equipment breakdowns. We formulate the problem as a mixed-integer nonlinear program which maximizes the total profit for the whole system. The model simultaneously determines the number and location of facilities, the subset of customers to serve, the assignment of customers to facilities, and the cycle-order quantities at facilities. In order to obtain near-optimal solutions with reasonable computational requirements for large problem instances, two solution methods based on Lagrangian relaxation and genetic algorithm are developed. The effectiveness of the proposed solution approaches is shown using numerical experiments. The computational results, in addition, demonstrate that the benefits of considering disruptions in the supply chain design model can be significant.

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