Parallel-machine scheduling methodology for a multi-dock truck sequencing problem in a cross-docking center

Nogueira, Thiago Henrique; Coutinho, Felipe Provezano; Ribeiro, Rafael Pereira; Ravetti, Martı́n Gómez

doi:10.1016/j.cie.2020.106391

Cited by 13 publications

(26 citation statements)

References 33 publications

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“…e main contribution of the paper is the Lagrangian decay diagram for the structured integer linear model of the problem. Reference [17] studied the problem of sequencing multiterminal trucks in a cross-connected hub with the aim of minimizing production time, and they came up with a parallel machine scenario. Instead of the traditional stream stores setup and proposes a polynomial parallel machine-based heuristic method that outperforms time-indexed math formulas and modern heuristics for small, medium, and large cases big (Shahmardan and Sajadieh [18], they proposed simulated annealing as a solution method.…”

Section: Literature Reviewmentioning

confidence: 99%

A Multiobjective Mathematical Model for Truck Scheduling Problem in Multidoor Cross‐Docking System

Taghizadeh

Shojaie

Sarfaraz

et al. 2022

Discrete Dynamics in Nature and Society

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Cross-docking is the main operation of unloading products from incoming trucks, regrouping products in relation to their destination, and loading directly onto shipping trucks, reducing warehousing, picking, transportation costs, and delivery times. This is the intended logistics technology. In this paper, we present a new bi-objective mixed-integer mathematical model for truck scheduling problems in cross-docking systems. The goal of the proposed mixed-integer mathematical model is to minimize the total operation time (makespan) and cost of moving cargo within the terminal. The performance of the proposed model is compared with that of the available model to solve small instances. The results showed that in solving small size of problem, the proposed model in this study is more efficient and we found better solutions. An evolutionary algorithm called the nondominated sorting genetic algorithm (NSGA-II) has been proposed to solve larger instances due to computational complexity. To evaluate the proposed algorithm, a comparative analysis of benchmark instances was performed and the efficiency of the above algorithm was compared to the nondominated ranked algorithm (NRGA) based on the index designed in the literature. The statistical hypothesis testing (t-test) is used for determining the best algorithm based on the average runtime and average number of Pareto solutions. Using the Taguchi method, the proposed algorithms are tuned. Considering a temporary storage space and the multiple receiving and shipping docks is the main contribution of the paper. Finally, for evaluating algorithms, multicriteria decision-making (MCDM) technique and statistical method are used. The results show the suitable performance of presented model.

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Section: Literature Reviewmentioning

confidence: 99%

A Multiobjective Mathematical Model for Truck Scheduling Problem in Multidoor Cross‐Docking System

Taghizadeh

Shojaie

Sarfaraz

et al. 2022

Discrete Dynamics in Nature and Society

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“…They focused on optimizing truck-to-door sequencing with the intention of rehashing the truck holding pattern in inbound trucks in order to minimize makespan. Nogueira et al (2020) [40] proposed an approach dependent on the parallel machine environment for the cross-docking issue. Nikzamir and Baradaran (2020) [41] proposed a novel healthcare waste location-routing problem with another point of view in medical services coordination organization.…”

Section: Introductionmentioning

confidence: 99%

Modelling Cross-Docking in a Three-Level Supply Chain with Stochastic Service and Queuing System: MOWFA Algorithm

2022

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In today’s competitive world, it is essential to provide a new method through which maximum efficiency can be created in the production and supply cycle. In many production environments, sending goods directly from the producer to the consumer brings many problems. Therefore, an efficient transport system should be established between producers and consumers. Such a system is designed in the field of supply chain management knowledge. Supply chain management is the evolutionary result of warehousing management and is one of the important infrastructural foundations of business implementation, in many of which the main effort is to shorten the time between the customer’s order and the actual delivery of the goods. In this research, the supply chain consists of three levels. Suppliers are placed on the first level, cross-docks on the second level, and factories on the third level. In this system, a number of suppliers send different raw materials to several different cross-docks. Each channel is assigned to a cross-dock for a specific product. The main goal of this article is to focus on optimizing the planning of incoming and outgoing trucks with the aim of minimizing the total operation time within the supply chain. The arrival rate of goods from suppliers to the cross-dock is stochastic with a general probability distribution. On the other hand, the time required to prepare and send the goods is random with a general probability distribution. The service time in each cross-dock depends on the number of its doors. Therefore, each cross-dock can be modeled as a G/G/m queueing system where m represents the number of doors. The mathematical model of the research has been developed based on these assumptions. Since the problem is NP-hard, the time to solve it increases drastically with the increase in the dimensions of the problem. Therefore, three metaheuristics, including multi-objective water flow, non-dominated sorting genetic, and a multi-objective simulated annealing algorithm have been used to find near-optimal solutions to the problem. After adjusting the parameters of the algorithms using the Taguchi method, the results obtained from the algorithms were analyzed with a statistical test and the performance of the algorithms was evaluated. The results vividly demonstrate that non-dominated sorting genetics is the best of all.

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“…Similarly, [11] also applied the idea to their cases with the addition of time-indexed variables. The problem was approached by using constructive polynomial-time algorithm and more traditional scheduling algorithm like Johnson's rule-based algorithm [12]. The topic also consists of works from works from [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

“…The problem was approached by using constructive polynomial-time algorithm and more traditional scheduling algorithm like Johnson's rule-based algorithm [12]. The topic also consists of works from works from [11][12][13][14]. The work of [14] was constructed predicated on the work of [10] on the two-stage hybrid cross-docking scheduling.…”

Section: Introductionmentioning

confidence: 99%

A Truck Scheduling Problem for Multi-Crossdocking System with Metaheuristics

Phuc¹,

Thanh²,

Tram³

2022

Computers, Materials &Amp; Continua

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The cross-docking is a very important subject in logistics and supply chain managements. According to the definition, cross-docking is a process dealing with transhipping inventory, in which goods and products are unloaded from an inbound truck and process through a flow-center to be directly loaded onto an outbound truck. Cross-docking is favored due to its advantages in reducing the material handing cost, the needs to store the product in warehouse, as well decreasing the labor cost by eliminating packaging, storing, pick-location and order picking. In cross-docking, products can be consolidated and transported as a full load, reducing overall distribution costs. In this paper, we focus on a truck scheduling at the multidoor, multi-crossdocking network with inventory constraints and process capability constraints. In this model, a truck can visit severals docks for loading or unloading many types products. This situation is very common in reality. This study also developed an exact mathematical model using mixedinteger linear programming (MILP) with the objective of minimizing the makespan to obtaint the benchmark in small scale problems. Large scale problems are solved through Simulated Annealing (SA) algorithm and Tabu Search (TS) algorithm. Performance of these algorithms will be compared to benchmarks obtained from solver as well as to each other.

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Parallel-machine scheduling methodology for a multi-dock truck sequencing problem in a cross-docking center

Cited by 13 publications

References 33 publications

A Multiobjective Mathematical Model for Truck Scheduling Problem in Multidoor Cross‐Docking System

A Multiobjective Mathematical Model for Truck Scheduling Problem in Multidoor Cross‐Docking System

Modelling Cross-Docking in a Three-Level Supply Chain with Stochastic Service and Queuing System: MOWFA Algorithm

A Truck Scheduling Problem for Multi-Crossdocking System with Metaheuristics

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