Biofuel Supply Chain Optimization Using Lévy-Enhanced Swarm Intelligence

2020 ◽  
pp. 169-197
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Optimization Techniques ◽  
Optimal Decision ◽  
Supply Chain Optimization ◽  
Industrial Systems ◽  
Planning Optimization ◽  
Biofuel Supply Chain ◽  
Solution Methods ◽  
Optimal Decision Making

Supply chain planning/optimization presents various challenges to decision makers globally due to its highly complicated nature as well as its large-scale structure. Over the years various state-of-the-art methods have been employed to model supply chains. Optimization techniques are then applied to such models to help with optimal decision making. However, with highly complex industrial systems such as these, conventional metaheuristics are still plagued by various drawbacks. Strategies such as hybridization and algorithmic modifications have been the focus of previous efforts to improve the performance of conventional metaheuristics. In light of these developments, this chapter presents two solution methods for tackling the biofuel supply chain problem.

Multiobjective Optimization of a Biofuel Supply Chain Using Random Matrix Generators

2020 ◽  
pp. 206-232 ◽  
Author(s):  
Timothy Ganesan ◽  
Pandian Vasant ◽  
Igor Litvinchev
Keyword(s):  
Supply Chain ◽  
Random Matrix ◽  
Large Scale ◽  
Cuckoo Search ◽  
Optimization Techniques ◽  
Computational Results ◽  
Matrix Approach ◽  
Industrial Systems ◽  
Biofuel Supply Chain ◽  
Effective Design

As industrial systems become more complex, various complexities and uncertainties come into play. Metaheuristic-type optimization techniques have become crucial for effective design, maintenance, and operations of such systems. However, in highly complex industrial systems, conventional metaheuristics are still plagued by various drawbacks. Strategies such as hybridization and algorithmic modifications have been the focus of previous efforts to improve the performance of conventional metaheuristics. This work tackles a large-scale multi-objective (MO) optimization problem: biofuel supply chain. Due to the scale and complexity of the problem, the random matrix approach was employed to modify the stochastic generator segment of the cuckoo search (CS) technique. Comparative analysis was then performed on the computational results produced by the conventional CS technique and the improved CS variants.

Lévy-Enhanced Swarm Intelligence for Optimizing a Multiobjective Biofuel Supply Chain

2020 ◽  
pp. 287-309 ◽  
Author(s):  
T. Ganesan ◽  
Pandian Vasant
Keyword(s):  
Supply Chain ◽  
Swarm Intelligence ◽  
Large Scale ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Cuckoo Search ◽  
Biofuel Supply Chain ◽  
Solution Methods ◽  
The Face ◽  
Chain Problem

Engineering systems are currently plagued by various complexities and uncertainties. Metaheuristics have emerged as an essential tool for effective engineering design and operations. Nevertheless, conventional metaheuristics still struggle to reach optimality in the face of highly complex engineering problems. Aiming to further boost the performance of conventional metaheuristics, strategies such as hybridization and various enhancements have been added into the existing solution methods. In this work, swarm intelligence techniques were employed to solve the real-world, large-scale biofuel supply chain problem. Additionally, the supply chain problem considered in this chapter is multiobjective (MO) in nature. Comparative analysis was then performed on the swarm techniques. To further enhance the search capability of the best solution method (GSA), the Lévy flight component from the Cuckoo Search (CS) algorithm was incorporated into the Gravitational Search Algorithm (GSA) technique; developing the novel Lévy-GSA technique. Measurement metrics were then utilized to analyze the results.

Biofuel Supply Chain Optimization Using Random Matrix Generators

2020 ◽  
pp. 198-215
Keyword(s):  
Supply Chain ◽  
Random Matrix ◽  
Large Scale ◽  
Supply Chain Optimization ◽  
Heavy Atoms ◽  
Large Scale Problems ◽  
Biofuel Supply Chain

Supply chain problems are large-scale problems with complex interlinked variables. This sort of characteristic closely resembles structures often encountered in the nuclei of heavy atoms (e.g., platinum, gold or rhodium). Such structures are said to have the property of universality.

Supply chain optimization of large-scale continuous processes

2005 ◽  
Vol 29 (6) ◽  
pp. 1305-1316 ◽  
Author(s):  
E.P. Schulz ◽  
M.S. Diaz ◽  
J.A. Bandoni
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Supply Chain Optimization ◽  
Continuous Processes

Operation decision of logistics service supply chain: considering interruption probability in emergencies

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Guangsheng Zhang ◽  
Xiao Wang ◽  
Zhiqing Meng ◽  
Qirui Zhang ◽  
Kexin Wu
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Evolutionary Game ◽  
Optimal Strategies ◽  
Optimal Decision ◽  
Content Type ◽  
Logistics Service ◽  
Social Reputation ◽  
Punishment Intensity ◽  
Optimal Decision Making

PurposeTo remedy the inherent defect in current research that focuses only on a single type of participants, this paper endeavors to look into the situation as an evolutionary game between a representative Logistics Service Integrator (LSI) and a representative Functional Logistics Service Provider (FLSP) in an environment with sudden crisis and tries to analyze how LSI supervises FLSP's operations and how FLSP responds in a recurrent pattern with different interruption probabilities.Design/methodology/approachRegarding the risks of supply chain interruption in emergencies, this paper develops a two-level model of single LSI and single FLSP, using Evolutionary Game theory to analyze their optimal decision-making, as well as their strategic behaviors on different risk levels regarding the interruption probability to achieve the optimal return with bounded rationality.FindingsThe results show that on a low-risk level, if LSI increases the degree of punishment, it will fail to enhance FLSP's operational activeness in the long term; when the risk rises to an intermediate level, a circular game occurs between LSI and FLSP; and on a high level of risk, FLSP will actively take actions, and its functional probability further impacts LSI's strategic choices. Finally, this paper analyzes the moderating impact of punishment intensity and social reputation loss on the evolutionary model in emergencies and provides relevant managerial implications.Originality/valueFirst, by taking both interruption probability and emergencies into consideration, this paper explores the interactions among the factors relevant to LSI's and FLSP's optimal decision-making. Second, this paper analyzes the optimal evolutionary game strategies of LSI and FLSP with different interruption probability and the range of their optimal strategies. Third, the findings of this paper provide valuable implications for relevant practices, such that the punishment intensity and social reputation loss determine the optimal strategies of LSI and FLSP, and thus it is an effective vehicle for LSSC system administrator to achieve the maximum efficiency of the system.

scholarly journals Supply chain optimization with variable demand by considering financial criteria and scenarios

2017 ◽  
Vol 26 (44) ◽  
pp. 21 ◽  
Author(s):  
John Willmer Escobar
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Net Present Value ◽  
Programming Model ◽  
Supply Chain Design ◽  
Mixed Integer ◽  
Supply Network ◽  
Distribution Centers ◽  
Supply Chain Optimization ◽  
Starting Point

This paper contemplates the supply chain design problem of a large-scale company by considering the maximization of the Net Present Value. In particular, the variability of the demand for each type of product at each customer zone has been estimated. As starting point, this paper considers an established supply chain for which the main problem is to determine the decisions regarding expansion of distribution centers. The problem is solved by using a mixed-integer linear programming model, which optimizes the different demand scenarios. The proposed methodology uses a scheme of optimization based on the generation of multiple demand scenarios of the supply network. The model is based on a real case taken from a multinational food company, which supplies to the Colombian and some international markets. The obtained results were compared with the equivalent present costs minimization scheme of the supply network, and showed the importance and efficiency of the proposed approach as an alternative for the supply chain design with stochastic parameters.

scholarly journals Customer Knowledge Enabled Innovation: Analyzing Pricing-Promotion Coordination Mechanism

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Guanbing Zhao ◽  
Yangyang Qiu ◽  
Muhammad Imran ◽  
Fazal Manan
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Repeated Game ◽  
Consumer Electronics ◽  
Coordination Mechanism ◽  
Optimal Decision ◽  
Consumer Electronic ◽  
Market Launch ◽  
Optimal Decision Making ◽  
New Consumer

Pricing and promotion are two important decisions during the market launch of new consumer electronics products. Nowadays, the pricing and promotion of consumer electronic products are often not made separately but at the same time. This study focuses on the pricing-promotion coordination mechanism of a secondary supply chain of new consumer electronics products (which consists of a manufacturer and a seller). Price and the degree of promotion together affect the demand for products. Manufacturers give sellers a sales target. Manufacturers and sellers set prices and promotions separately, introduce repurchase penalty joint contracts, and establish supply chain profit models to compare and analyze optimal pricing, promotion efforts, and maximum profit of supply chains under different decision-making situations. We prove that the repurchase penalty joint contract can coordinate the supply chain under the assumptions of a single-period game and a multiperiod repeated game. The results show that under the repurchase penalty joint contract, when manufacturers and sellers choose high prices and high promotions at the same time, the supply chain of new consumer electronics products has the largest profit. Finally, numerical experiments are conducted to study the influence of parameters on optimal decision-making and supply chain profits.

Measuring Shared and Team Situation Awareness of Emergency Decision Makers

2012 ◽  
Vol 4 (4) ◽  
pp. 1-15 ◽  
Author(s):  
Yasir Javed ◽  
Tony Norris
Keyword(s):  
Situation Awareness ◽  
Large Scale ◽  
Systems Design ◽  
Optimal Decision ◽  
Team Members ◽  
Decision Performance ◽  
Emergency Managers ◽  
Team Situation Awareness ◽  
Optimal Decision Making ◽  
Emergency Decision

Large scale emergencies are usually responded to by a team of emergency managers or a number of sub teams. Team coordination has attracted considerable research interest, especially from the cognitive, human factors, and ergonomic aspects because the shared situation awareness (SSA) and team situation awareness (TSA) of team members is critical for optimal decision making. This paper describes the development of an information system (SAVER) based on SSA and TSA oriented systems design. Validation and evaluation of the implemented design shows that decision performance is improved by the SAVER system.

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