A solution algorithm for integrated production-inventory-routing of perishable goods with transshipment and uncertain demand

Лю, Пэйдэ; Hendalianpour, Ayad; Razmi, Jafar; Sangari, Mohamad Sadegh

doi:10.1007/s40747-020-00264-y

Cited by 37 publications

(31 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Liu et al [38] Probabilistic Robust optimization method Inventory-routing Kumar et al [35] Quadrilateral fuzzy number Fuzzy programming SCN Present study IFN Fuzzy bi-level multi-objective SCN…”

Section: Logistic Transportationmentioning

confidence: 99%

Significance of multi-objective optimization in logistics problem for multi-product supply chain network under the intuitionistic fuzzy environment

Gupta

Haq

Ali

et al. 2021

Complex Intell. Syst.

View full text Add to dashboard Cite

Determining the methods for fulfilling the continuously increasing customer expectations and maintaining competitiveness in the market while limiting controllable expenses is challenging. Our study thus identifies inefficiencies in the supply chain network (SCN). The initial goal is to obtain the best allocation order for products from various sources with different destinations in an optimal manner. This study considers two types of decision-makers (DMs) operating at two separate groups of SCN, that is, a bi-level decision-making process. The first-level DM moves first and determines the amounts of the quantity transported to distributors, and the second-level DM then rationally chooses their amounts. First-level decision-makers (FLDMs) aimed at minimizing the total costs of transportation, while second-level decision-makers (SLDM) attempt to simultaneously minimize the total delivery time of the SCN and balance the allocation order between various sources and destinations. This investigation implements fuzzy goal programming (FGP) to solve the multi-objective of SCN in an intuitionistic fuzzy environment. The FGP concept was used to define the fuzzy goals, build linear and nonlinear membership functions, and achieve the compromise solution. A real-life case study was used to illustrate the proposed work. The obtained result shows the optimal quantities transported from the various sources to the various destinations that could enable managers to detect the optimum quantity of the product when hierarchical decision-making involving two levels. A case study then illustrates the application of the proposed work.

show abstract

Section: Logistic Transportationmentioning

confidence: 99%

Significance of multi-objective optimization in logistics problem for multi-product supply chain network under the intuitionistic fuzzy environment

Gupta

Haq

Ali

et al. 2021

Complex Intell. Syst.

View full text Add to dashboard Cite

show abstract

“…They presented an anticipatory customer assignment policy, which is able to improve service significantly for all stakeholders. To solve an integrated problem of production-inventory-routing of perishable goods with transshipment and uncertain demand, Liu et al [28] presented an algorithm that begins with an initial solution and then iteratively improves it using two local search strategies including inserting the best and removing the worst solutions. In [30], Liu considered on-demand meal delivery service using drones, and proposed a progressive algorithm for drone dispatch and order delivery in a dynamic, realtime operational environment.…”

Section: Related Workmentioning

confidence: 99%

Hybrid evolutionary optimization for takeaway order selection and delivery path planning utilizing habit data

Zhang

et al. 2021

Complex Intell. Syst.

View full text Add to dashboard Cite

The last years have seen a rapid growth of the takeaway delivery market, which has provided a lot of jobs for deliverymen. However, increasing numbers of takeaway orders and the corresponding pickup and service points have made order selection and path planning a key challenging problem to deliverymen. In this paper, we present a problem integrating order selection and delivery path planning for deliverymen, the objective of which is to maximize the revenue per unit time subject to maximum delivery path length, overdue penalty, reward/penalty for large/small number of orders, and high customer scoring reward. Particularly, we consider uncertain order ready time and customer satisfaction level, which are estimated based on historical habit data of stores and customers using a machine-learning approach. To efficiently solve this problem, we propose a hybrid evolutionary algorithm, which adapts the water wave optimization (WWO) metaheuristic to evolve solutions to the main order selection problem and employs tabu search to route the delivery path for each order selection solution. Experimental results on test instances constructed based on real food delivery application data demonstrate the performance advantages of the proposed algorithm compared to a set of popular metaheuristic optimization algorithms.

show abstract

“…Biuki et al [22] modeled a specific type of integrated PDP for perishable goods with inventory, location, and routing decisions by realworld data. Liu et al [23] recently considered the integrated PDP in a blood SC containing one supplier and some blood centers while the transshipment among the blood centers was allowed.…”

Section: Literature Reviewmentioning

confidence: 99%

A Bi-objective Robust Optimization Model for an Integrated Production-distribution Problem of Perishable Goods with Demand Improvement Strategies: A Case Study

Aazami

Saidi‐Mehrabad

Seyedhosseini

2021

IJE

View full text Add to dashboard Cite

This paper develops a bi-objective optimization model for the integrated production-distribution planning of perishable goods under uncertainty. The first objective seeks to maximize the profit in a specific supply chain with three levels: plants, distribution centers, and in the last level, customers. Since transportation is one of the major pollution sources in a distribution problem, the second objective is to minimize their emission. In the considered problem, the decisions of production, location, inventory, and transportation are made in an integrated structure. In developing the demand function, the effect of the product freshness and the price is formulated. Besides, to encourage customers, three strategies, including perished product return, discount, and credit policies, are proposed. Also, robust optimization is utilized to cope with the operational uncertainty of some cost parameters. To prove the applicability of this research and the feasibility of the environmental aspect, a case study is conducted. Finally, the numerical computations on the case study provide a trade-off between the environmental and economic goals and indicate a 37.5 percent increase in the profit using the developed model.

show abstract

A solution algorithm for integrated production-inventory-routing of perishable goods with transshipment and uncertain demand

Cited by 37 publications

References 53 publications

Significance of multi-objective optimization in logistics problem for multi-product supply chain network under the intuitionistic fuzzy environment

Significance of multi-objective optimization in logistics problem for multi-product supply chain network under the intuitionistic fuzzy environment

Hybrid evolutionary optimization for takeaway order selection and delivery path planning utilizing habit data

A Bi-objective Robust Optimization Model for an Integrated Production-distribution Problem of Perishable Goods with Demand Improvement Strategies: A Case Study

Contact Info

Product

Resources

About