Journal Article

·2005

A heuristic approach using multiple criteria for environmentally benign 3PLs selection

Elif Kongar YTU

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE

Abstract

Maintaining competitiveness in an environment where price and quality differences between competing products are disappearing depends on the company's ability to reduce costs and supply time. Timely responses to rapidly changing market conditions require an efficient Supply Chain Management (SCM). Outsourcing logistics to third-party logistics service providers (3PLs) is one commonly used way of increasing the efficiency of logistics operations, while creating a more "core competency focused" business environment. However, this alone may not be sufficient. Due to recent environmental regulations and growing public awareness regarding environmental issues, 3PLs need to be not only efficient but also environmentally benign to maintain companies' competitiveness. Even though an efficient and environmentally benign combination of 3PLs can theoretically be obtained using exhaustive search algorithms, heuristics approaches to the selection process may be superior in terms of the computational complexity. In this paper, a hybrid approach that combines a multiple criteria Genetic Algorithm (GA) with Linear Physical Weighting Algorithm (LPPW) to be used in efficient and environmentally benign 3PLs is proposed. A numerical example is also provided to illustrate the method and the analyses.

Keywords

Outsourcing Computer science Environmentally friendly Heuristics Heuristic Service provider Weighting Supply chain Process (computing) Quality (philosophy) Selection (genetic algorithm) Genetic algorithm Service (business) Operations research Business Marketing Artificial intelligence

Subject Areas

Sustainable Supply Chain Management ·Strategy and Management ·Social Sciences
Multi-Criteria Decision Making ·Management Science and Operations Research ·Social Sciences
RFID technology advancements ·Media Technology ·Physical Sciences

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Responsible consumption and production 42%