Number Of Pallets Research Articles

Different Approaches for Performance Appraisal and Bonus Calculation: The Case of Truck Drivers

Market changes last years have led to an additional understanding of people importance as the main resources of companies. Truck drivers are one of the occupations with the greatest shortage. More attention is being paid to ways of retaining employees. One of the most important measures is bonus or reward. There is a lack of models in the literature and it is exactly the main motive of this research. Proposed models create a basis for future theoretical research, but also for practical applications. The main assumption is that models must provide a fair way to earn bonuses in a "healthy environment". Two models are proposed. The first model for distribution company with a heterogeneous fleet of vehicles with less capacity. The second model refers to homogenous heavy truck fleet. In the first case, several criteria are used: distance (kilometers) driven, number of tours/rides, number of unloading stops and number of pallets. The second model is based on fuel consumption, distance driven, vehicle maintenance, driver experience (years in the company) and overall dispatcher score. The results show the convenience of applying the proposed models. Certain differences were also identified in the observed models. It can be concluded that there is no universal model for performance appraisal and bonus calculation. Ideas for overcoming and improving models are also proposed. Described models in original or adapted form can be applied to evaluate the performance of drivers in a wide variety of transport systems.

Multi-container loading problems with multidrop and split delivery conditions

This paper considers a multi-container loading problem in which each customer orders a set of pallets of different weights and the objective is to meet all orders with the minimum number of trucks. Strict constraints regarding stability, multidrop, and axle weight limits must be respected for each truck at each stop along the route. When assigning pallets to trucks, split delivery is allowed, even if each customer’s order fits on a single truck.Determining the minimum number of trucks in container loading, considering realistic packing constraints and allowing for split delivery, is a challenging problem that has not been addressed in the literature. To solve it optimally, we first develop an integer linear model and then a decomposition procedure, combining relaxed integer models and heuristic algorithms. An extensive computational study on a new benchmark, varying the number of customers, the number of pallets, and the pallet weight configurations, showed that the integer linear model could only solve small instances, but the decomposition procedure was capable of efficiently solving all instances to optimality. The benchmark was also used to study the effect of split delivery on the solutions of the problem, determining in which cases it provides advantages compared to the non-split alternative in terms of feasibility and number of trucks.

The pallet-loading vehicle routing problem with stability constraints

This paper addresses an integrated routing and loading problem in which the pallets ordered by a set of customers have to be delivered by a set of trucks so that the total distance traveled is minimized. The problem has two main distinctive features. On the one hand, when assigning pallets to trucks, strict packing constraints, concerning axle weight, stability, and sequential loading, must be considered. On the other hand, split delivery is allowed.We have developed an integer linear model for the integrated problem, considering all routing and packing constraints. We have also designed a more efficient decomposition procedure in which some packing constraints are initially relaxed. Each time an integer solution is found in the search tree of the relaxed problem, it is checked to see whether it satisfies the remaining constraints and is therefore a feasible solution to the original problem. If it is not, a heuristic algorithm is first applied to rearrange the solution and, if it fails, an integer model is used, considering the packing problem for a single truck. If this also fails, a constraint is added to the relaxed problem to cut off the infeasible integer solution.An extensive computational study shows how the integer linear model and the decomposition procedure work on a set of instances varying the number of customers, the number of pallets, and their weight distribution.

Perspective large-capacity containers

Analysis and comparison of existing types of large-capacity containers and containers of new sizes. The layout of two main types of pallets in large-volume containers is presented. Number of pallets and maximum pallet weight calculated for each layout and type of large container

Mathematical models and heuristic algorithms for pallet building problems with practical constraints

AbstractIn the pallet building problem, we aim at loading a given set of items into one or more pallets, by satisfying specific constraints and minimizing the number of pallets used. In this paper, we address a practical case of this problem that originates from a real-world robotized application, subject to some non-trivial operational constraints. In practice, items are grouped into families and must be packed into horizontal layers. To facilitate loading/unloading operations, items of the same type packed into the same layer should be contiguous and at least one of them should be visible from the outside. We present a formal mathematical description for layer and pallet creation subproblems and then we propose heuristic, metaheuristic, matheuristic algorithms to solve the overall problem. The performance of the algorithms is assessed through extensive computational tests on real-world instances.

Bin packing with lexicographic objectives for loading weight- and volume-constrained trucks in a direct-shipping system

We consider a packing problem that arises in a direct-shipping system in the food and beverage industry: Trucks are the containers, and products to be distributed are the items. The packing is constrained by two independent quantities, weight (e.g., measured in kg) and volume (number of pallets). Additionally, the products are grouped into the three categories: standard, cooled, and frozen (the latter two require refrigerated trucks). Products of different categories can be transported in one truck using separated zones, but the cost of a truck depends on the transported product categories. Moreover, splitting orders of a product should be avoided so that (un-)loading is simplified. As a result, we seek for a feasible packing optimizing the following objective functions in a strictly lexicographic sense: minimize the (1) total number of trucks; (2) number of refrigerated trucks; (3) number of refrigerated trucks which contain frozen products; (4) number of refrigerated trucks which also transport standard products; (5) and minimize splitting. This is a real-world application of a bin-packing problem with cardinality constraints a.k.a. the two-dimensional vector packing problem with additional constraints. We provide a heuristic and an exact solution approach. The heuristic meta-scheme considers the multi-compartment and item fragmentation features of the problem and applies various problem-specific heuristics. The exact solution algorithm covering all five stages is based on branch-and-price using stabilization techniques exploiting dual-optimal inequalities. Computational results on real-world and difficult self-generated instances prove the applicability of our approach.

Optimization of the Time Durations by Exploiting Time Margins in Time Interval Models

Considering time interval models, which can describe a large class of models including timed event graphs and P-time event graphs, a general aim is to control the system such that it follows a one-periodic behavior starting from an initial state with a minimal or maximal cycle time. The aim of this article is the optimization of the time durations in order to achieve a given rate of production when the quantity of resources (number of pallets, machines, and so on), usually represented by the initial marking, is assumed to be a fixed datum. A prior step is the determination of the critical subsystems, whose variations can influence these optimal values and affect the obtainment of the relevant trajectories and the noncritical subsystems leading to time margins. Two approaches are proposed in that aim. A first technique is based on an adaptation of the classical Martínez and Silva’s algorithm, where each solution gives a critical subsystem, while a second approach checks each inequality of the system by an optimality verification. Using this partition of the subsystems and particularly exploiting the time margins corresponding to idle times of machines, the approach allows an optimization of the noncritical time durations when the extremum cycle times and the resources are the constant parameters of the problem. In this article, the definition of P-time event graphs is generalized by introducing the model of time supervisor place, which restricts the time behavior of a set of places. The approach is applied to a plant bakery composed of two production lines.

Genetic Algorithm Based Storage and Retrieval System Optimization Considering Operational Constraints in a Multidimensional Warehouse

Efficient use of warehouse resources is an important issue that makes them more manageable and useful, also helps product flow faster. In multidimensional warehouses with many constraints such as weight, volume, product compatibility, etc., storage and retrieval processes are complex optimization problems that need to be solved. Considering the number of constraints, the solution to the storage and retrieval problems with traditional algorithms take a long time. Meta-heuristic algorithms are frequently used in the solution of many complex optimization problems as they can provide acceptable solutions in a short time. In this study, the Genetic algorithm which is one of the popular meta-heuristic methods was used to solve this problem, and the A-star algorithm was used to travel the shortest path between the shelves. A three-dimensional warehouse with operational constraints was designed. Storage and retrieval orders containing a different number of pallets were produced randomly to perform warehouse product flow, and some of these orders were assumed as storage requests and the remainder were retrieval requests. Results show that the proposed approach is capable of finding effective solutions for storage and retrieval problems with operational constraints in a short time.

On the hardness of palletizing bins using FIFO queues

We study the combinatorial FIFO Stack-Up problem. In the delivery industry, bins have to be moved from conveyor belts onto pallets. Given is a list Q of k sequences of labeled bins and a positive integer p. The goal is to palletize the bins by iteratively removing the first bin of one of the k sequences and putting it onto a pallet located at one of p stack-up places. Each of these pallets has to contain bins of only one label, bins of different labels have to be placed on different pallets. After all bins of one label have been removed from the given sequences, the corresponding stack-up place becomes available for a pallet of bins of another label. The FIFO Stack-Up problem asks whether such a processing is possible. The FIFO Stack-Up problem is known to be NP-complete even if the sequences of Q contain together at most cQ=6 bins per pallet. This implies that the problem is also hard if all bins of every pallet are distributed to at most dQ=6 sequences. In this paper we strengthen the hardness to the cases cQ=5 and dQ=3. We also show the hardness for the practical case where the number of sequences is smaller than the number of pallets, and we point out differences to related problems like 3D Bin Packing and Train Marshalling.

Simulation analysis of multi-node manufacturing system under design and scheduling strategies

To cater for dynamic and variable performance matrices, manufacturing industries use automation tools and technologies to impart manufacturing flexibility in their processes. To successfully cater for its performance, manufacturing requirements should be designed into the system and then appropriate planning and operational policies need to be followed to support it. This research work validates this using an industrial size flexible manufacturing system (FMS) as a multi-node manufacturing framework having eight machines. While FMS design spectrum is modelled by different levels of its routing flexibility (RF) and number of pallets (NP), planning and operational strategies are implemented through various combinations of dispatching and sequencing rules (DR/SR). This work is a simulation study to evaluate FMS performance for which makes time (MST) and machine utilisation have been used as a performance metric. This research provides a framework for the decision makers in identifying the appropriate levels of routing flexibility, number of pallets and appropriate combination of dispatching and sequencing rules for optimising system performance under a given manufacturing environment.

A hybrid genetic and imperialist competitive algorithm for green vendor managed inventory of multi-item multi-constraint EOQ model under shortage

The purpose of this paper is to develop a multi-item economic order quantity (EOQ) model with shortage for a single-buyer single-supplier supply chain under green vendor managed inventory (VMI) policy. This model explicitly includes the VMI contractual agreement between the vendor and the buyer such as warehouse capacity and delivery constraints, bounds for each order, and limits on the number of pallets. To create a kind of green supply chain, tax cost of green house gas (GHG) emissions and limitation on total emissions of all items are considered in the model. A hybrid genetic and imperialist competitive algorithm (HGA) is employed to find a near-optimum solution of a nonlinear integer-programming (NIP) with the objective of minimizing the total cost of the supply chain. Since no benchmark is available in the literature, a genetic algorithm (GA) is developed as well to validate the result obtained. For further validation, the outcomes are also compared to lower bounds that are found using a relaxed model in which all variables are treated continuous. At the end, numerical examples are presented to demonstrate the application of the proposed methodology. Our results proved that the proposed hybrid procedure was able to find better and nearer optimal solutions.

Impact of manufacturing flexibility and pallets on buffer delay in flexible manufacturing systems

In the current competitive scenario, it is essential to consider a manufacturing system which supports increased flexibility and automation. Flexible manufacturing system (FMS) is one such alternative to meet the product variety condition and demand uncertainty. In this paper, Taguchi experimental design framework is used to evaluate the effect of varying levels of manufacturing flexibility (routing and machine) and number of pallets on the delay at buffers in an FMS. The effects of other factors such as scheduling rules (sequencing and dispatching) are also investigated. Results of simulation study indicate that number of pallets and routing flexibility are the two most important factors affecting the average delay at buffers (ADB); however, there is an optimal combination of factors which minimises the delay at buffers under the given set of operating conditions.

Sustainable and Robust Control of Cyclic Pallet Systems

A proper control of a system to get a desired function and increase the system lifetime is a crucial step towards the sustainable paradigm. In this paper, such a control is designed for a cyclic pallet system to achieve a minimal force on its drive unit, meet safety conditions on the system chain tension force, and the momentum of pallets, and fulfill a desired production rate. The optimal values of control parameters, namely, number of pallets, conveyor velocity, and part set schedule, are obtained through solving a mixed integer linear optimization model. The objective function in the model defines the average force on the drive unit in a cycle production. In addition, the related constraints characterize the pallet system properties such as cyclic and dynamic behavior, buffer size, constant work in process, and safety specifications. This optimization model strongly suffers from the time complexity due to the binary decision variables defining the part set schedule. To reasonably handle the computation time, a heuristic search strategy based on a modified form of the weighted profile fitting algorithm is introduced. Furthermore, the robustness of the optimal control and the system design is analyzed, using worst control and worst but safe control strategies. The optimal control and the robustness analysis are applied to some case studies, and the results are evaluated and discussed.

Workflow scheduling using multi-agent systems in a dynamically changing environment

The application of intelligent agent technologies is considered a promising approach to improve system performance in complex and changeable environments. Especially, in the case of unforeseen events, for example, machine breakdowns that usually lead to a deviation from the initial production schedule, a multi-agent approach can be used to enhance system flexibility and robustness. In this paper we apply this approach to revise and re-optimize the dynamic system schedule in response to unexpected events. We employ Multi-Agent System simulation to optimize the total system output (eg, number of finished products) for recovery from machine and/or conveyor failure cases. Diverse types of failure classes (conveyor and machine failures), as well as duration of failures are used to test a range of dispatching rules in combination with the All Rerouting re-scheduling policy, which showed supreme performance in our previous studies. In this context, the Critical Ratio rule, which includes the transportation time into the calculation for the selection of the next job, outperformed all other dispatching rules. We also analysed the impact of diverse simulation parameters (such as number of pallets, class of conveyor failure and class of machine failure) on the system effectiveness. Presented research also enlightens the economic interdependencies between the examined parameters and the benefits of using the agent paradigm to minimize the impact of the disrupting events on the dynamic system.

Modelos matemáticos para problemas de dimensionamento de lotes com restrições de capacidade e custos de transporte

Neste trabalho estudam-se problemas de dimensionamento de lotes em que as decisões clássicas do dimensionamento dos lotes de produção são tomadas considerando também os custos do transporte dos produtos fabricados. Estes custos estão associados ao número de paletes ou caminhões necessários para empacotar e/ou transportar os produtos produzidos desde a fábrica até o depósito. São consideradas três extensões de um modelo de programação inteira mista, apresentado na literatura, representando casos mais gerais que ocorrem na prática. Estes modelos são testados e avaliados usando um pacote de otimização. Também é apresentado um método heurístico de resolução, baseado em relaxação Lagrangiana, para uma das extensões propostas.

Interval analysis to optimise a production line of pharmaceuticals

In this paper, we focus on optimisation through simulation of a production line and packaging of pharmaceuticals. Precisely, we propose to couple our simulation model with an optimisation algorithm to determine the optimal number of pallets to insert in the conveyors to maximise the production rate. The idea of the proposed optimisation algorithm is original. It is based on an iterative division of the interval of possible solutions.

Simulation of a Closed-Loops Assembly Line

The aim of the work presented in this paper describes the development of a decision support system based on a discrete-event simulation model of an automobile assembly line. The model focuses at a very specific class of production lines with a four closed-loop network configuration. One key characteristic in the closed-loop system is that the number of pallets inside the first three loops has been made constant. The impact of the number of pallets circulating on the first three closed-loops and of the proportion of four-door car bodies on the performance of the production line has been thoroughly investigated. This has been translated into the number of cars produced per hour, in order to improve the availability of the entire manufacturing system.

Simulation for Transport Pallet Cost Reduction in Pet Food Manufacturing: An Empirical Case Study

SUMMARYThis study examined different managerial scenarios for the cost reduction of transport pallets rented by a pet food manufacturer that produces pet food sold in local and international markets. A computer simulation model was developed on the basis of the empirical case to analyse the flow of pallets from the factory, the subcontractors and the distribution centre and to determine the system performance measures in terms of the average waiting times and the number of pallets in queues. The analysis showed that problems occurred when slow‐moving products occupied the rental pallets for a long time and because too much inventory was kept at the distribution centre. Two managerial scenarios were then proposed to alleviate these problems, involving pallet movement decisions by internal management. The results suggested a choice of decision supports to determine which managerial scenario was suitable for the business. The proposed implications may be beneficial to similar industries where a supply system of rental pallet service is applied. Copyright © 2011 John Wiley & Sons, Ltd.

A heuristic approach to scheduling jobs in machining centres equipped with automated pallet changers

We present a heuristic algorithm for scheduling jobs in a machining centre equipped with multiple-pallet automated pallet changers (APCs). The algorithm dynamically adjusts the number of pallets used and the priority of each job to minimise the total weighted tardiness. The algorithm was evaluated based on a study conducted at Vaxjofabriken, a metal-casting company located in Vaxjo, Sweden. Results obtained from this study show more than a 40% reduction in the total weighted tardiness of the overall machining park.

Effect of Scheduling and Manufacturing Flexibility on the Performance of FMS

A framework for studying the effect of scheduling and manufacturing flexibility on the performance of flexible manufacturing system has been presented in this paper. Scheduling and manufacturing flexibility are among the many manufacturing strategies considered by the researchers to improve the system performance. In this paper in addition to scheduling and manufacturing flexibility other manufacturing strategies being considered are system configuration, buffer capacity, routing flexibility (manufacturing flexibility), number of pallets, volume of parts, dispatching and sequencing rules (scheduling). Performance of systems is evaluated on make-span time, cost, machine utilization and queue waiting time. The key issues which are addressed in this paper are the impact of different levels of routing flexibility, dispatching and sequencing rules and the increase in number of pallets on the system performance. Simulation results indicate that, with increase in routing flexibility, make-span time decreases. However the maximum benefit is obtained when routing flexibility increased from level 1 to 2. Combinations of sequencing and dispatching rules are identified, which can yield best results for make-span, cost of production, queue waiting time and machine utilization. It is suggested that the proposed methodology can be used in practice for not only setting priorities on specific manufacturing factors but also for highlighting likely factor level combinations that could yield improved shop performance.