A routing and scheduling problem for cross-docking networks with perishable products, heterogeneous vehicles and split delivery

Shahabi-Shahmiri, Reza; Tavakkoli–Moghaddam, Reza; Mousavi, Seyed Meysam; Rajabzadeh, Mohsen

doi:10.1016/j.cie.2021.107299

Cited by 31 publications

(9 citation statements)

References 78 publications

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“…Multiobjective methods for vehicle routing and scheduling problems within supply chain problems have been studied recently by Rahbari et al ( 2019 ), Goodarzi et al ( 2020 ), and Shahabi-Shahmiri et al ( 2021 ). A bi-objective MILP model for the vehicle routing and scheduling problem with cross-docking for perishable products has been studied by Rahbari et al ( 2019 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Two-stage optimization scheme of routing scheduling from a single distribution center to multiple customers

2023

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This paper proposes a solution scheme for the problem of scheduling deliveries from distribution centers. The solution scheme is developed in two phases. The first phase corresponds to the collection and processing of data, and the second phase includes the design of a customer assignment model based on the data of the first phase. The first phase provides the characteristics of the customers, the number of orders to be dispatched, and the number of visited customers. In the second phase, optimization techniques are used, considering scheduling and assignment problem-solving methodologies. The optimization model provides the correct assignment of customer orders to vehicles, reducing the number of trips and the fleet's size and occupation percentage. The proposed solution scheme is developed with a company operating a distribution center responsible for dispatching vehicles to all retail customers, wholesalers, and distributors in the Province of Concepción, Province of Arauco, and Province of Itata in Chile. The obtained results are prominent and show that the proposed methodology can be extended to companies performing storage, transportation, and distribution tasks with similar characteristics.

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Section: Literature Reviewmentioning

confidence: 99%

Two-stage optimization scheme of routing scheduling from a single distribution center to multiple customers

2023

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“…The transportation problem for agricultural products has been widely studied by many researchers [20][21][22][23][24][25][26][27][28]. Agricultural products are typically perishable.…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Artificial Multiple Intelligence System (AMIS) for Agricultural Product Transborder Logistics Network Design in the Greater Mekong Subregion (GMS)

et al. 2022

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In recent years, agriculture products have contributed to 28.75% of Thailand’s GDP. China, Vietnam, Myanmar, Cambodia, Laos and Vietnam are the main markets for agricultural products. The annual export volume exceeds 119,222 million THB. The majority of them are shipped over Thailand’s land borders to its neighbors. Small and medium-sized farmers make up more than 85% of those who produce agricultural items. Numerous scholars have studied the transportation methods used by the Greater Mekong Subregion (GMS) nations along the economic corridor, but the majority of them have concentrated on import–export operations involving sizable firms, which are not applicable to the transportation of agricultural products, particularly when attention is paid to small and medium-sized farmers. In this study, mixed-integer programming (MIP) is presented to design an agricultural product logistics network. In order to prolong the lifespan of the container used, the MIP’s primary goal is to maximize the total chain profit while maintaining the lowest container usage possible. The approach was developed to increase small and medium-sized farmers’ ability to compete. Small and medium-sized farmers bring their products to an agricultural product collecting center, also known as a container loading facility. After that, skilled logistics companies distribute the goods. In order to convey the goods to the final clients in neighboring nations, the proper locations of the containing loading centers, the correct transportation option and the borders must be decided. The issue was identified as multi-echelon location–allocation sizing (MELLS), an NP-hard problem that cannot be handled in an efficient manner. To solve a real-world problem, however, efficient techniques must be supplied. AMIS, an artificial multiple intelligence system, was created to address the suggested issue. AMIS was developed with the goal of leveraging a variety of methods for local search and development. There are several well-known heuristics techniques employed in the literature, including the genetic algorithm (GA) and the differential evolution algorithm (DE). With respect to the improved solutions obtained, the computational results show that AMIS exceeds the present heuristics, outperforming DE and GA by 9.34% and 10.95%, respectively. Additionally, the system’s farmers made a total of 15,236,832 THB in profit, with an average profit per container of 317,434 THB and an average profit per farmer of 92,344.44 THB per crop. The container loading center uses 48 containers, with a 5.33 container average per container loading center (CLC). The farmers’ annual revenues were previously less than 88,402 THB per family per year, so we can predict that the new network may increase customers’ annual income by 4.459% for each crop.

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“…However, heterogeneous vehicles and numerous route combinations make manual scheduling difficult. In order to solve this problem, Shahabi-Shahmiri et al (2021) propose a new multi-objective mixed-integer programming model to minimize the transportation cost. In Zlot and Stentz's (2005) research, the scheduling problem of coupled tasks that need two types of robots' cooperation is simplified by a task tree based decomposition algorithm.…”

Section: Introductionmentioning

confidence: 99%

Multi-decision points model to solve coupled-task scheduling problem with heterogeneous multi-AGV in manufacturing systems

Wang¹,

Wu²,

Xing³

2023

10.5267/j.ijiec

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Automated guided vehicle (AGV) is widely used in automated manufacturing systems as a material handling tool. Although the task scheduling problem with isomorphic AGV has remained a very active research field through the years, too little work has been devoted to the task scheduling problems with heterogeneous AGVs. A coupled task with heterogeneous AGVs is a complex task that needs the cooperation of more than one type of AGVs. In this paper, a manufacturing system with two types of AGVs and three types of tasks is studied. To solve the coupled task scheduling problem with heterogeneous AGVs in this manufacturing system, we introduce two new methods based on the established mathematical model, namely, the decoupled scheduling strategy and coupled scheduling strategy with multi-decision model. The decoupled scheduling strategy is widely used in coupled task scheduling problems. However, there are some situations that the decoupled scheduling strategy cannot solve the problem well. To overcome the problem, the multi-decision point model solves the coupled task scheduling problem without decomposition. In order to ensure the searching speed and searching accuracy, a novel hybrid heuristic algorithm based on simulated annealing algorithm and tabu search algorithm is developed. The simulation experiment results show the proposed coupled scheduling algorithm has priority in coupled task scheduling problems.

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A routing and scheduling problem for cross-docking networks with perishable products, heterogeneous vehicles and split delivery

Cited by 31 publications

References 78 publications

Two-stage optimization scheme of routing scheduling from a single distribution center to multiple customers

Two-stage optimization scheme of routing scheduling from a single distribution center to multiple customers

A Novel Artificial Multiple Intelligence System (AMIS) for Agricultural Product Transborder Logistics Network Design in the Greater Mekong Subregion (GMS)

Multi-decision points model to solve coupled-task scheduling problem with heterogeneous multi-AGV in manufacturing systems

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