An iterative approach for a bi-level competitive supply chain network design problem under foresight competition and variable coverage

Amiri, Alireza Shamekhi; Torabi, S. Ali; Ghodsi, Reza

doi:10.1016/j.tre.2017.11.002

Cited by 24 publications

(5 citation statements)

References 46 publications

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“…e methods of genetic meta-heuristic, simulated annealing, and memetic algorithm were used to solve the proposed model. Amiri et al [18] presented a multistage model for distribution, routing, and inventory control under uncertainty. Minimizing service time, the cost of establishing relief centers and inventory costs were among the objectives of this study.…”

Section: Literature Reviewmentioning

confidence: 99%

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Presenting a Management Model for a Multiobjective Sustainable Supply Chain in the Cellulosic Industry and Its Implementation by the NSGA‐II Meta‐Heuristic Algorithm

Charvadeh

Pourmousa

Tajdini

et al. 2022

Discrete Dynamics in Nature and Society

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In recent years, with changing conditions in global markets and competition between supply chains, organizations have realized that in order to grow and survive in today’s turbulent environment, they must make every effort to create and maintain a sustainable competitive advantage. Therefore, in this research, a multiobjective, multilevel, multiperiod, and multicommodity mathematical model is presented. The proposed model has five levels in the direct direction and three levels in the reverse direction. This research is one of the few studies that has considered the sustainable closed-loop supply chain of cellulosic-based products (paper and corrugated board) in the model and has considered it at all levels of the chain. Also, the quality of returned products in the reverse supply chain and its impact on the collection and recycling of products and returning to the supply chain are other contributions of this research. The results show, by increasing the transportation costs, the number of established distribution centers increases to a certain extent and finally remains constant. As it is shown, the reduction of transportation costs to the point of establishing four centers in the recession scenario and five centers in the boom scenario becomes saturated and is no longer able to minimize the number of established centers.

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Section: Literature Reviewmentioning

confidence: 99%

“…Constraint (17) indicates the quantity of products sent from the manufacturer to the distributor. Constraint (18) indicates that demand must be fully met. Constraint (19) indicates the capacity of suppliers.…”

Section: Variablesmentioning

confidence: 99%

Presenting a Management Model for a Multiobjective Sustainable Supply Chain in the Cellulosic Industry and Its Implementation by the NSGA‐II Meta‐Heuristic Algorithm

Charvadeh

Pourmousa

Tajdini

et al. 2022

Discrete Dynamics in Nature and Society

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“…(1988). In recent years, both exact algorithms and hybrid heuristics are proposed for a bi‐level optimization problem, including a branch‐and‐cut algorithm (Quadros et al., 2018), an iterative global search method (Shamekhi Amiri et al., 2018), and simulated annealing heuristics (Ghaffarinasab and Motallebzadeh, 2017). For instance, Quadros et al.…”

Section: Solution Approachmentioning

confidence: 99%

“…Shamekhi Amiri et al. (2018) propose an iterative global search method through incorporating the possible reaction of the follower in the leader's problem as new constraints (i.e., cuts) in each iteration. Soares et al.…”

Section: Solution Approachmentioning

confidence: 99%

A game‐theoretic approach for the location of terror response facilities with both disruption risk and hidden information

Gan

et al. 2020

Int Trans Operational Res

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Recently, locating emergency response facilities has been drawing increasing attention with the highly strategic nature of terrorist attacks. To this end, we present a game‐theoretic approach for the location of terror response facilities when both disruption risk and hidden information are taken into account. The game is described as a two‐stage game, in which the first stage allows the State, that is, defender, to locate the terror response facilities, including disclosed and undisclosed facilities, and assign them to the attacked city, while the second stage allows the terrorist, that is, attacker, to select one city to attack with partial information about facility location and assignment. We propose a mixed integer bi‐level nonlinear programming formulation, and in response, a heuristic algorithm is developed to find the equilibrium solution. Extensive computational tests on both synthetic data and a real‐world dataset of provincial capital cities in China demonstrate the effectiveness of the developed algorithm.

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“…They also presented four algorithms to obtain an optimal trade-o between the objective function values of the two levels. In the last paper we reviewed, but certainly not the latest research conducted on the BLP, Shamekhi Amiri et al [46] developed a BLP for two competitive SCs under foresight competition and variable coverage. They proposed an iterative global search approach that inserted, in each iteration, the reaction of the follower in the leader's problem as new constraints.…”

Section: Review Of the Literature On Bi-level Programming And Pricingmentioning

confidence: 99%

Benders Decomposition Algorithm for Robust Aggregate Production Planning Considering Pricing Decisions in Competitive Environment: A Case Study

Aazami

Saidi‐Mehrabad

2018

Scientia Iranica

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In operations research, bi-level programming is a mathematical modeling which has another optimization problem as a constraint. In the present research, regarding the current intense competition among large manufacturing companies for achieving a greater market share, a bi-level robust optimization model is developed as a leader-follower problem using Stackelberg game in the eld of Aggregate Production Planning (APP). The leader company with higher in uence intended to produce new products, which could replace the existing products. The follower companies, as rivals, were also seeking more sales, but they did not have the intention and ability to produce such new products. The price of the new products was determined by the presented elasticity relations between uncertain demand and price. After linearization, using the KKT conditions, the bi-level robust model was transformed into an ordinary uni-level model. Due to the NP-hard nature of the problem, Benders Decomposition Algorithm (BDA) was proposed for overcoming the computational complexities in large scale. Finally, using the real data of Sarvestan Sepahan Co as a leader company, the validity of the developed model as well as e ciency and convergence of the BDA was investigated. The computational results clearly showed the e ciency and e ectiveness of the proposed BDA.

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An iterative approach for a bi-level competitive supply chain network design problem under foresight competition and variable coverage

Cited by 24 publications

References 46 publications

Presenting a Management Model for a Multiobjective Sustainable Supply Chain in the Cellulosic Industry and Its Implementation by the NSGA‐II Meta‐Heuristic Algorithm

Presenting a Management Model for a Multiobjective Sustainable Supply Chain in the Cellulosic Industry and Its Implementation by the NSGA‐II Meta‐Heuristic Algorithm

A game‐theoretic approach for the location of terror response facilities with both disruption risk and hidden information

Benders Decomposition Algorithm for Robust Aggregate Production Planning Considering Pricing Decisions in Competitive Environment: A Case Study

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