scholarly journals Mathematical Optimization Model for Truck Scheduling in a Distribution Center with a Mixed Service-Mode Dock Area

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Gustavo Correa Issi ◽  
Rodrigo Linfati ◽  
John Willmer Escobar
Keyword(s):  
Mathematical Optimization ◽  
Distribution Center ◽  
Mixed Integer ◽  
Cross Docking ◽  
Truck Scheduling ◽  
Logistics Strategy ◽  
Service Mode ◽  
Reducing Costs ◽  
And Storage

Cross-docking is a logistics strategy in which products arriving at a distribution center are unloaded from inbound trucks and sorted for transfer directly to outbound trucks, reducing costs and storage and product handling times. This paper addresses a cross-docking problem by designing a mixed-integer linear programming (MILP) model to determine a schedule for inbound and outbound trucks in a mixed service-mode dock area that minimizes the time from when the first inbound truck arrives until the last outbound truck departs (makespan). The model is developed using AMPL software with the CPLEX and Gurobi solvers, which provide results for different instances, most of these with actual shift data from an integrated distribution center of a multinational food company located in Concepción, Chile. The results obtained from the case study are notable and show the effectiveness of the proposed mathematical model.

scholarly journals Combined Use of Mathematical Optimization and Design of Experiments for the Maximization of Profit in a Four-Echelon Supply Chain

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-25 ◽  
Author(s):  
Daniel Arturo Olivares Vera ◽  
Elias Olivares-Benitez ◽  
Eleazar Puente Rivera ◽  
Mónica López-Campos ◽  
Pablo A. Miranda
Keyword(s):  
Supply Chain ◽  
Design Of Experiments ◽  
Mathematical Optimization ◽  
Fractional Factorial ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Cost Component ◽  
Allocation Model

This paper develops a location-allocation model to optimize a four-echelon supply chain network, addressing manufacturing and distribution centers location, supplier selection and flow allocation for raw materials from suppliers to manufacturers, and finished products for end customers, while searching for system profit maximization. A fractional-factorial design of experiments is performed to analyze the effects of capacity, quality, delivery time, and interest rate on profit and system performance. The model is formulated as a mixed-integer linear programming problem and solved by using well-known commercial software. The usage of factorial experiments combined with mathematical optimization is a novel approach to address supply chain network design problems. The application of the proposed model to a case study shows that this combination of techniques yields satisfying results in terms of both its behavior and the obtained managerial insights. An ANOVA analysis is executed to quantify the effects of each factor and their interactions. In the analyzed case study, the transportation cost is the most relevant cost component, and the most relevant opportunity for profit improvement is found in the factor of quality. The proposed combination of methods can be adapted to different problems and industries.

scholarly journals Synthesis of Sustainable Carbon Negative Eco-Industrial Parks

2021 ◽  
Vol 9 ◽  
Author(s):  
Elizabeth J. Abraham ◽  
Farah Ramadan ◽  
Dhabia M. Al-Mohannadi
Keyword(s):  
Carbon Dioxide ◽  
Circular Economy ◽  
Carbon Dioxide Emissions ◽  
Carbon Capture ◽  
Carbon Dioxide Emission ◽  
Value Added ◽  
Mixed Integer ◽  
Industrial Parks ◽  
And Storage

Growing climate change concerns in recent years have led to an increased need for carbon dioxide emission reduction. This can be achieved by implementing the concept of circular economy, which promotes the practice of resource conservation, emission minimization, and the maintenance of sustainable revenue streams. A considerable amount of carbon dioxide emissions is a consequence of stationary sources from industrial processes. These emissions can be reduced using carbon capture utilization and storage (CCUS) or reduced at source by using emission free renewable resources. The method developed within this work uses mixed integer linear programming (MILP) to design sustainable clusters that convert seawater (including waste brine), air, and waste carbon dioxide emissions to value-added products with sunlight as the main energy source. In this way, circular economy is employed to minimize fresh resource consumption and maximize material reuse. The potential of this work is demonstrated through a case study, which shows that an industrial park may be profitable while adhering to strict emission and material constraints.

scholarly journals Improved Harmony Search Algorithm for Truck Scheduling Problem in Multiple-Door Cross-Docking Systems

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Zhanzhong Wang ◽  
Yue Lu ◽  
Liying Zhao ◽  
Ningbo Cao
Keyword(s):  
Mixed Integer Linear Programming ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Mixed Integer ◽  
Cross Docking ◽  
Truck Scheduling ◽  
Improved Harmony Search ◽  
The Cross ◽  
Improved Harmony Search Algorithm

The key of realizing the cross docking is to design the joint of inbound trucks and outbound trucks, so a proper sequence of trucks will make the cross-docking system much more efficient and need less makespan. A cross-docking system is proposed with multiple receiving and shipping dock doors. The objective is to find the best door assignments and the sequences of trucks in the principle of products distribution to minimize the total makespan of cross docking. To solve the problem that is regarded as a mixed integer linear programming (MILP) model, three metaheuristics, namely, harmony search (HS), improved harmony search (IHS), and genetic algorithm (GA), are proposed. Furthermore, the fixed parameters are optimized by Taguchi experiments to improve the accuracy of solutions further. Finally, several numerical examples are put forward to evaluate the performances of proposed algorithms.

The Optimal Allocation of Unloading/Loading Ramps in Distribution Centers

2015 ◽  
Vol 809-810 ◽  
pp. 1366-1371
Author(s):  
Sergiu Olteanu ◽  
Florin Valentin Rusca ◽  
Mircea Augustin Rosca ◽  
Eugen Rosca
Keyword(s):  
Optimal Allocation ◽  
Optimization Techniques ◽  
Distribution Center ◽  
Distribution Centers ◽  
Optimal Arrangement ◽  
Cargo Handling ◽  
Total Distance ◽  
Cross Docking ◽  
Handling Cost

Warehousing enables the consolidation of shipments to clients by assembling full truck loads from goods stored in warehouse or distribution center. Storage can be efficiently replenished by ordering full truck loads from suppliers. In order to reduce freight storage and handling costs from distribution centers, cross-docking technique represents a logistic solution which is more and more used. Thus, the optimization of simultaneous unloading/loading operations constitutes an important issue for the distribution center owner/administrator. This paper presents a model based on genetic algorithms optimization techniques for solving the problem of unloading/loading ramps allocation. The efficiency of a cross-docking center is conditioned practically by finding an allocation and an optimal arrangement of ramps. This implies the allocation of destinations to unloading/loading ramps of distribution centers to minimize the total distance performed by the the cargo handling equipment. The case study presents a cross-docking platform with single handling equipment which is assigned to 10 unloading/loading ramps. By applying the solution of the ramp allocation generated through simulation, the total distance performed by the handling equipment is reduced which means lower handling cost for the distribution center owner/administrator.

A truck scheduling problem at a cross-docking facility with mixed service mode dock doors

2019 ◽  
Vol 36 (6) ◽  
pp. 1977-2009 ◽  
Author(s):  
Behnam Vahdani ◽  
Shayan Shahramfard
Keyword(s):  
Heuristic Algorithms ◽  
Time Window ◽  
Content Type ◽  
Arrival Times ◽  
Cross Docking ◽  
Truck Scheduling ◽  
Service Mode ◽  
Time Window Constraints ◽  
Competitive Algorithms ◽  
Novel Model

Purpose The purpose of this study is truck scheduling and assignment of trucks to the doors simultaneously since these issues were considered mainly separately in the previous research. Also, the door service time and its impact on truck scheduling were not taken into account, so this research endeavors to cover this gap. Design/methodology/approach In this research, a novel model has been presented for simultaneous truck scheduling and assignment problem with time window constraints for the arrival and departure of trucks, mixed service mode dock doors and truck queuing. To resolve the developed model, two meta-heuristic algorithms, namely, genetic and imperialist competitive algorithms, are presented. Findings The computational results indicate that the proposed framework leads to increased total costs, although it has a more accurate planning; moreover, these indicate that the proposed algorithms have different performances based on the criteria considered for the comparison. Research limitations/implications There are some limitations in this research, which can be considered by other researchers to expand the current study, among them the specifications of uncertainty about arrival times of inbound and outbound trucks, number of merchandises which has been loaded on inbound trucks are the main factors. If so, by considering this situation, a realistic scheme about planning of cross docking system would be acquired. Moreover, the capacity of temporary storage has been considered unlimited, so relaxing this limitation can prepare a real and suitable situation for further study. Examining the capacity in the front of each type of doors of cross-dock and executive servers are the other aspects, which could be expanded in the future. Originality/value In this study, a mathematical programing model proposed for truck scheduling to minimize total costs including holding, truck tardiness and waiting time for queue of trucks caused by the interference of each carrier’s movement. At the operational levels, this research considered a multi-door cross-docking problem with mixed service mode dock doors and time window constraints for arrival and departure time of trucks. Moreover, M/G/C queue system was developed for truck arrival and servicing of carriers to trucks.

scholarly journals A mathematical model for truck-door assignment and product placement problem in cross-docking center

2017 ◽  
Vol 7 (1) ◽  
pp. 135-142
Author(s):  
İlker Küçükoğlu ◽  
Nursel Öztürk
Keyword(s):  
Mathematical Model ◽  
Real Life ◽  
Product Placement ◽  
Mixed Integer ◽  
Placement Problem ◽  
Long Term Storage ◽  
Cross Docking ◽  
Logistics Strategy ◽  
Logistics Company ◽  
Real Life Data

In today’s cross-docking offers a significant cost benefits to companies because of the small orders and frequent deliveries in logistical environment. Cross-docking is a relatively new logistics strategy in which items are moved from suppliers to customers through cross-docking centers without putting them into long-term storage. One of the fundamental issues in cross-docking facility is to assign the incoming and outgoing trucks to the doors in order to minimize movement of the products. This paper addresses the truck-door assignment problem of cross-docking centers with product placement plans and proposes a mixed integer mathematical model to solve problem. The objective of the mathematical model is to find best truck-door assignment and product placement plans that minimize total travelling distance of the products. The proposed model is tested on a problem set which are created by using a real-life data of a logistics company. The computational results show that the proposed mathematical model can be carried out for the real-life operations to minimize movement costs of the products in cross-docking centers. Keywords: Cross-docking, truck-door assignment, product placement, mathematical modelling; 

Choosing a Distribution Center to Improve the Vietnamese Fruit and Vegetable Supply Chain by the Hybrid Applied Mathematical Optimization and SAW

2020 ◽  
Author(s):  
Kieu Phan ◽  
Phong Ho
Keyword(s):  
Supply Chain ◽  
Survey Methods ◽  
Mathematical Optimization ◽  
Mekong Delta ◽  
Secondary Data ◽  
Distribution Center ◽  
Mixed Integer ◽  
Distribution Centers ◽  
Fruit And Vegetable ◽  
Simple Additive Weighting

Abstract In the current market economic conditions, the distribution center plays an important role in the the supply chain’s operation, especially when the fruit and vegetable supply chains in Vietnam still do not have a suitable distribution center, leading to high arrival costs and slow shipping times. Therefore, researching and proposing a model to locate distribution centers, contributing to cost reduction of the fruit and vegetable supply chain is a crucial issue in Vietnam today. Therefore, using many survey methods such as in-depth interview, focus groups, face-to-face to collect a total of 439 samples in Vinh Long province, as well as secondary data from new articles, studies, research articles, other authentic sources directing the administration of provincial statistical management and yearbooks for analyzing the sweet potato supply chain in Vinh Long province of the Mekong Delta region. First, this study used mixed-integer linear programming and compromised programming based on IBM CPLEX Optimizer to choose a distribution center when trading-off between cost and transport time. Secondly, Simple Additive Weighting (SAW) for decision support based on excel software from the results of experts’ answering to increase the objectivity for determining the location of the Distribution Center as well as in accordance with both the actual situation and the comprehensive development of local socio-economy. The contribution of proposing the mathematical model is to choose a suitable place for saving costs and reducing transport times. In additon, this approach method could be applied to other Vietnamese agri-fresh products for upgrading the competitiveness, compared with other countries' agricultural products in terms of price and quality so far.

scholarly journals A Decomposition Strategy for Optimal Design of a Soda Company Distribution System

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
J. A. Marmolejo ◽  
I. Soria ◽  
H. A. Perez
Keyword(s):  
Distribution System ◽  
Large Scale ◽  
Programming Model ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Computational Time ◽  
Fixed Costs ◽  
Distribution Centers ◽  
Cross Docking

This work presents a distribution problem of products of a soda bottling company. Commodities are produced at several plants with limited capacity and the demand of distribution centers is satisfied by shipping via cross-docking warehouses. The decomposition strategy is proposed to determine which warehouse needs to be opened to consolidate the demand and by which warehouse each distribution center is served exclusively. The objective is minimizing fixed costs and total transportation costs. The model presented is a mixed-integer programming model with binary variables for which we propose a decomposition strategy based on Benders algorithm. Numerical results show that the proposed strategy can provide the optimal solution of several instances. A large-scale case study based on a realistic company situation is analyzed. Solutions obtained by the proposed method are compared with the solution of full scale problem in order to determine the quality bound and computational time.

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