Strategic-Level Robust Optimal Design Method of Product Family and Supply Chain Network

2018 ◽  
Author(s):  
Masato Toi ◽  
Kana Sawai ◽  
Yutaka Nomaguchi ◽  
Kikuo Fujita
Keyword(s):  
Supply Chain ◽  
Design Problem ◽  
Design Method ◽  
Product Family ◽  
Optimal Solution ◽  
Computational Method ◽  
Mixed Integer ◽  
Mathematical Framework ◽  
Integer Programming Problem ◽  
Supply Chain Network

Manufacturing firms must meet a wide variety of customer needs flexibly and effectively. Thus, simultaneous design of the product family and the supply chain network is required. This design problem must be assessed in terms of strategic-level decision making under uncertainties without any detailed and fixed information on the design conditions. We therefore propose a mathematical framework by considering the optimal profitability and robustness against destructive incidences. This paper discusses the design problem structure and formulates it as a mixed-integer programming problem. A computational method is configured for solving the optimization problem, in which only profitability is considered as the objective. A procedure to assess the robustness of the profitability-oriented optimal solution is proposed by evaluating the Pareto optimality among the nominal optimal solution and its competitive solutions. A case study of a coffee maker product family design problem is demonstrated to verify the proposed framework.

scholarly journals An integrated location-inventory model for a spare part’s supply chain considering facility disruption risk and CO2 emission

2021 ◽  
Vol 14 (2) ◽  
pp. 87
Author(s):  
Rubayet Karim ◽  
Koichi Nakade
Keyword(s):  
Supply Chain ◽  
Co2 Emission ◽  
Spare Part ◽  
Spare Parts ◽  
Inventory Model ◽  
Mixed Integer ◽  
Integer Programming Problem ◽  
Supply Chain Network ◽  
Emission Level ◽  
Disruption Risk

Purpose: Managing the inventory of spare parts is very difficult because of the stochastic nature of part’s demand. Also, only controlling the inventory of the spare part is not enough; instead, the supply chain of the spare part needs to be managed efficiently. Moreover, every organization now aims to have a resilient and sustainable supply chain to overcome the risk of facility disruption and to ensure environmental sustainability. This paper thus aims to establish a model of inventory-location relating to the resilient supply chain network of spare parts.Design/methodology/approach: First, applying queuing theory, a location-inventory model for a spare parts supply chain facing a facility disruption risk and has a restriction for CO2 emission, is developed. The model is later formulated as a non-linear mixed-integer programming problem and is solved using MATLAB.Findings: The model gives optimal decisions about the location of the warehouse facility and the policy of inventory management of each location selected. The sensitivity analysis shows that the very low probability of facility disruption does not influence controlling the average emission level. However, the average emission level certainly decreases with the increment of the disruption probability when the facility disruption probability is significant.Practical implications: Using this model, based on the cost and emission parameters and the likelihood of facility disruption, the spare part’s manufacturer can optimize the total average cost of the spare part’s supply chain through making a trade-off between productions, warehouse selection, inventory warehousing and demand allocation.Originality/value: Previous research focuses only on developing a framework for designing an efficient spare parts planning and control system. The inventory-location model for spare parts is not addressed in the sense of risk of facilities disturbance and emission. This research first time jointly considered the probabilistic facility disruption risk and carbon emission for modeling the spare part’s supply chain network.

scholarly journals A Modified Priority-Based Encoding for Design of a Closed-Loop Supply Chain Network Using a Discrete League Championship Algorithm

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Javid Ghahremani Nahr ◽  
Ramez Kian ◽  
Hassan Rezazadeh
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Closed Loop ◽  
Optimal Solution ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Numerical Comparison ◽  
Supply Chain Network ◽  
Closed Loop Supply Chain ◽  
Smooth Flow

In a closed-loop supply chain network, the aim is to ensure a smooth flow of materials and attaining the maximum value from returning and end-of-life goods. This paper presents a single-objective deterministic mixed integer linear programming (MILP) model for the closed-loop supply chain (CLSC) network design problem consisting of plants, collection centers, disposal centers, and customer zones. Our model minimizes the total costs comprising fixed opening cost of plants, collection, disposal centers, and transportation costs of products among the nodes. As supply chain network design problems belong to the class of NP-hard problems, a novel league championship algorithm (LCA) with a modified priority-based encoding is applied to find a near-optimal solution. New operators are defined for the LCA to search the discrete space. Numerical comparison of our proposed encoding with the existing approaches in the literature is indicative of the high quality performance of the proposed encoding.

Solving a Two-stage Supply Chain Network Design Problem with Fixed Costs by a Hybrid Genetic Algorithm

2021 ◽  
Author(s):  
Ovidiu Cosma ◽  
Petrică C Pop ◽  
Cosmin Sabo
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Network Design ◽  
Design Problem ◽  
Optimization Problem ◽  
Hybrid Genetic Algorithm ◽  
Network Design Problem ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Fixed Costs

Abstract In this paper we investigate a particular two-stage supply chain network design problem with fixed costs. In order to solve this complex optimization problem, we propose an efficient hybrid algorithm, which was obtained by incorporating a linear programming optimization problem within the framework of a genetic algorithm. In addition, we integrated within our proposed algorithm a powerful local search procedure able to perform a fine tuning of the global search. We evaluate our proposed solution approach on a set of large size instances. The achieved computational results prove the efficiency of our hybrid genetic algorithm in providing high-quality solutions within reasonable running-times and its superiority against other existing methods from the literature.

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.

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.

Physarum solver: a bio-inspired method for sustainable supply chain network design problem

2017 ◽  
Vol 254 (1-2) ◽  
pp. 533-552 ◽  
Author(s):  
Xiaoge Zhang ◽  
Andrew Adamatzky ◽  
Felix T. S. Chan ◽  
Sankaran Mahadevan ◽  
Yong Deng
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Design Problem ◽  
Network Design Problem ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Sustainable Supply Chain
Sign in / Sign up

Export Citation Format

Share Document