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Competitive pressure in the global marketplace inquires enterprises to establish efficiently distribution planning and inventory management in supply chain. This study proposes a framework to optimize distribution and inventory decisions integrating decisions of opening or closing facilities in multi-echelon supply chain network under non-stationary demand. The model adopts distribution requirements planning (DRP) technique and considers flexible distribution strategies, including multiple sourcing, drop shipping, and lateral transshipments to minimize the expected total cost. The original stochastic model has been simplified into the equivalent deterministic mixed-integer linear programming by following the sample average approximation (SAA) technique. Besides, the numerical experiments are conducted to validate the model and its practical application. The results indicate the model adopting multiple flexible distribution strategies outperforms the models adopting single distribution strategy. The study is applied for enterprises who sell products through their both physical stores and online stores on e-commerce platforms or the company’s private website.

Competitive pressure in the global marketplace inquires enterprises to establish efficiently distribution planning and inventory management in supply chain. This study proposes a framework to optimize distribution and inventory decisions integrating decisions of opening or closing facilities in multi-echelon supply chain network under non-stationary demand. The model adopts distribution requirements planning (DRP) technique and considers flexible distribution strategies, including multiple sourcing, drop shipping, and lateral transshipments to minimize the expected total cost. The original stochastic model has been simplified into the equivalent deterministic mixed-integer linear programming by following the sample average approximation (SAA) technique. Besides, the numerical experiments are conducted to validate the model and its practical application. The results indicate the model adopting multiple flexible distribution strategies outperforms the models adopting single distribution strategy. The study is applied for enterprises who sell products through their both physical stores and online stores on e-commerce platforms or the company’s private website.

Competitive pressure in the global marketplace inquires enterprises to establish efficiently distribution planning and inventory management in supply chain. This study proposes a framework to optimize distribution and inventory decisions integrating decisions of opening or closing facilities in multi-echelon supply chain network under non-stationary demand. The model adopts distribution requirements planning (DRP) technique and considers flexible distribution strategies, including multiple sourcing, drop shipping, and lateral transshipments to minimize the expected total cost. The original stochastic model has been simplified into the equivalent deterministic mixed-integer linear programming by following the sample average approximation (SAA) technique. Besides, the numerical experiments are conducted to validate the model and its practical application. The results indicate the model adopting multiple flexible distribution strategies outperforms the models adopting single distribution strategy. The study is applied for enterprises who sell products through their both physical stores and online stores on e-commerce platforms or the company’s private website.

Competitive pressure in the global marketplace inquires enterprises to establish efficiently distribution planning and inventory management in supply chain. This study proposes a framework to optimize distribution and inventory decisions integrating decisions of opening or closing facilities in multi-echelon supply chain network under non-stationary demand. The model adopts distribution requirements planning (DRP) technique and considers flexible distribution strategies, including multiple sourcing, drop shipping, and lateral transshipments to minimize the expected total cost. The original stochastic model has been simplified into the equivalent deterministic mixed-integer linear programming by following the sample average approximation (SAA) technique. Besides, the numerical experiments are conducted to validate the model and its practical application. The results indicate the model adopting multiple flexible distribution strategies outperforms the models adopting single distribution strategy. The study is applied for enterprises who sell products through their both physical stores and online stores on e-commerce platforms or the company’s private website.

Competitive pressure in the global marketplace inquires enterprises to establish efficiently distribution planning and inventory management in supply chain. This study proposes a framework to optimize distribution and inventory decisions integrating decisions of opening or closing facilities in multi-echelon supply chain network under non-stationary demand. The model adopts distribution requirements planning (DRP) technique and considers flexible distribution strategies, including multiple sourcing, drop shipping, and lateral transshipments to minimize the expected total cost. The original stochastic model has been simplified into the equivalent deterministic mixed-integer linear programming by following the sample average approximation (SAA) technique. Besides, the numerical experiments are conducted to validate the model and its practical application. The results indicate the model adopting multiple flexible distribution strategies outperforms the models adopting single distribution strategy. The study is applied for enterprises who sell products through their both physical stores and online stores on e-commerce platforms or the company’s private website.