scholarly journals Matheuristics for the Design of a Multi-Step, Multi-Product Supply Chain with Multimodal Transport

2021 ◽  
Vol 11 (21) ◽  
pp. 10251
Author(s):  
David A. Ruvalcaba-Sandoval ◽  
Elias Olivares-Benitez  ◽  
Omar Rojas ◽  
Guillermo Sosa-Gómez
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Exact Methods ◽  
Mixed Integer Linear Program ◽  
Global Networks ◽  
Four Levels

Supply-chain network design is a complex task because there are many decisions involved, and presently, global networks involve many actors and variables, for example, in the automotive, pharmaceutical, and electronics industries. This research addresses a supply-chain network design problem with four levels: suppliers, factories, warehouses, and customers. The problem considered decides on the number, locations, and capacities of factories and warehouses and the transportation between levels in the supply chain. The problem is modeled as a mixed-integer linear program. The main contribution of this work is the proposal of two matheuristic algorithms to solve the problem. Matheuristics are algorithms that combine exact methods and heuristics, attracting interest in the literature because of their fast execution and high-quality solutions. The matheuristics proposed to select the warehouses and their capacities following heuristic rules. Once the warehouses and their capacities are fixed, the algorithms solve reduced models using commercial optimization software. Medium and large instances were generated based on a procedure described in the literature. A comparison is made between the algorithms and the results obtained, solving the model with a time limit. The algorithms proposed are successful in obtaining better results for the largest instances in shorter execution times.

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.

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.

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
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