Nature-Inspired Intelligence in Supply Chain Management

2011 ◽  
pp. 1-31
Author(s):  
Vassilios Vassiliadis ◽  
Giorgos Dounias
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Optimization Problems ◽  
Real Life ◽  
Ant Colonies ◽  
Chain Management ◽  
Complex Optimization ◽  
Nature Inspired Intelligence ◽  
Optimum Solution

Supply chain management is a vital process for the competitiveness and profitability of companies. Supply chain consists of a large and complex network of components such as suppliers, warehouses, customers etc. which are connected in almost every possible way. Companies’ main aim is to optimize the components of these complex networks to their benefit. This constitutes a challenging optimization problem and often, traditional mathematical approaches fail to overcome complexity and to converge to the optimum solution. More robust methods are required sometimes in order to yield to the optimal. The field of artificial intelligence offers a great variety of meta-heuristic techniques which specialize in solving such complex optimization problems, either accurately, or by obtaining a practically useful approximation, even if real time constraints are imposed. The aim of this chapter is to present a survey of the available literature, regarding the use of nature-inspired methodologies in supply chain management problems. Nature-inspired intelligence is a specific branch of artificial intelligence. Its unique characteristic is the algorithmic imitation of real life systems such as ant colonies, flock of birds etc. in order to solve complex problems.

Supply Chain Modernization

2019 ◽  
pp. 168-176 ◽  
Author(s):  
Yasin Galip Gencer
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Real Life ◽  
Multinational Companies ◽  
Global Supply Chain ◽  
Organizational Changes ◽  
Chain Management ◽  
The Core ◽  
Operational Costs ◽  
External Entity

The global supply chain applications are evolving and changing globally. In order to increase success, some processes are now transferred to other firms. By such implementations, it is aimed to focus on the core business and to be successful. 3PL is the use of an external entity to perform some or all of the operations. The 4PL approach is a revolutionary approach to supply chain management. 3PL and 4PL activities are used for many purposes by multinational companies for increasing the productivity and efficiency and for decreasing the overall operational costs. Like all countries, Turkey also faces strategic organizational changes in terms of logistics activities. Modernization of logistic professes are widely examined in the literature. The scope of this chapter is the logistics modernization processes of Turkish companies, and it aims to inform about the modernization processes in Turkey by examining successful real-life examples.

Use of Information Technology in the Supply Chain Management of the Pharmaceutical Industry

2022 ◽  
pp. 137-168
Author(s):  
Saibal Kumar Saha ◽  
Sangita Saha ◽  
Ajeya Jha
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Cloud Computing ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Pharmaceutical Industry ◽  
Successful Implementation ◽  
Chain Management ◽  
Role Of Information

An efficient supply chain management helps to increase the productivity of a business. Use of information technology and concepts like artificial intelligence, blockchain, and cloud computing have integrated the different aspects of supply chain with its stakeholders. Published literature in the field of SCM, IT, and the pharmaceutical industry has been reviewed, and different aspects of innovation, technique, risks, advancements, factors, and models have been taken into consideration to form a comprehensive chapter focusing on the role of information technology in the supply chain management of the pharmaceutical industry. The chapter finds that IT has made a significant impact in improving the efficiency of SCM. But its successful implementation and collaboration with other firms is the key to success for an efficient SCM. Within each category, gaps have been identified.

Applications of artificial intelligence in the apparel industry: a review

2011 ◽  
Vol 81 (18) ◽  
pp. 1871-1892 ◽  
Author(s):  
ZX Guo ◽  
WK Wong ◽  
SYS Leung ◽  
Min Li
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Apparel Industry ◽  
Apparel Design ◽  
Research Issues ◽  
Chain Management ◽  
Research Challenges ◽  
State Of Art

This paper presents a systematic review on the state-of-art of artificial intelligence (AI) applications in the apparel industry. The existing literature is reviewed based on different research issues and AI-based methodologies. The research issues are categorized into four categories on the basis of the operation processes of the apparel industry, including apparel design, manufacturing, retailing, and supply chain management. This paper shows that research on AI applications in the apparel industry is still limited by analyzing the limitations of previous studies and research challenges. Finally, suggestions for further studies are offered.

scholarly journals The LR-Type Fuzzy Multi-Objective Vendor Selection Problem in Supply Chain Management

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1621
Author(s):  
Irfan Ali ◽  
Armin Fügenschuh ◽  
Srikant Gupta ◽  
Umar Muhammad Modibbo
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Real Life ◽  
Selection Problem ◽  
Programming Approach ◽  
Vendor Selection ◽  
Chain Management ◽  
Multi Objective ◽  
Fuzzy Environment ◽  
Proposed Model

Vendor selection is an established problem in supply chain management. It is regarded as a strategic resource by manufacturers, which must be managed efficiently. Any inappropriate selection of the vendors may lead to severe issues in the supply chain network. Hence, the desire to develop a model that minimizes the combination of transportation, deliveries, and ordering costs under uncertainty situation. In this paper, a multi-objective vendor selection problem under fuzzy environment is solved using a fuzzy goal programming approach. The vendor selection problem was modeled as a multi-objective problem, including three primary objectives of minimizing the transportation cost; the late deliveries; and the net ordering cost subject to constraints related to aggregate demand; vendor capacity; budget allocation; purchasing value; vendors’ quota; and quantity rejected. The proposed model input parameters are considered to be LR fuzzy numbers. The effectiveness of the model is illustrated with simulated data using R statistical package based on a real-life case study which was analyzed using LINGO 16.0 optimization software. The decision on the vendor’s quota allocation and selection under different degree of vagueness in the information was provided. The proposed model can address realistic vendor selection problem in the fuzzy environment and can serve as a useful tool for multi-criteria decision-making in supply chain management.

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