Fast Algorithms for Basic Supply Chain Scheduling Problems (original) (raw)
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Supply Chain Scheduling: Batching and Delivery
Operations Research, 2003
Although the supply chain management literature is extensive, the benefits and challenges of coordinated decision making within supply chain scheduling models have not been studied. We consider a variety of scheduling, batching, and delivery problems that arise in an arborescent supply chain where a supplier makes deliveries to several manufacturers, who also make deliveries to customers. The objective is to minimize the overall scheduling and delivery cost, using several classical scheduling objectives. This is achieved by scheduling the jobs and forming them into batches, each of which is delivered to the next downstream stage as a single shipment. For each problem, we either derive an efficient dynamic programming algorithm that minimizes the total cost of the supplier or that of the manufacturer, or we demonstrate that this problem is intractable. The total system cost minimization problem of a supplier and manufacturer who make cooperative decisions is also considered. We demon...
A branch and bound method for solving multi-factory supply chain scheduling with batch delivery
Expert Systems with Applications, 2015
This study addresses the scheduling of supply chain with interrelated factories containing suppliers and manufacturers. These elements of the chain are positioned in series and thus the efficient design of the link among them would insure good performance of the whole. In this paper, jobs transportation among factories and also delivery to the customer can be performed by batch of jobs. The capacity of each batch is limited and the cost per batch delivery is fixed and independent of the number of jobs in the batch. Thus decision should be made on the number of batches, assignment of each job to a batch and also production and delivery scheduling of batches in each factory. The problem scrutinization is on the tradeoff between minimizing transportation cost and tardiness cost. A branch and bound method for solving this problem is presented. A lower bound and a standalone heuristic which is used as an upper bound are also introduced. Computational tests are conducted to evaluate the performance of the proposed method.
Batch scheduling in customer-centric supply chains
Supply chain scheduling is a new emerging area of research. We study batch arrival scheduling problems at the manufacturer in a multi-level customer-centric supply chain, where promised job due dates are considered constraints which must be satisfied. We analyze the tradeoff between inventory holding costs and batch delivery costs. We show that the problems are closely related to batch scheduling problems on a single machine with flow-time related objectives. We prove that minimizing the sum of total weighted flow time and delivery costs is strongly NP-hard. For the unweighted version of the problem, we present efficient solution algorithms both for single machine and assembly systems. We also develop a dynamic programming solution for minimizing the sum of maximum flow time and delivery costs.
Metaheuristics for A New MINLP Model with reduced response time for On-line Order Batching
Scientia Iranica, 2019
Companies are looking for effective strategies to improve warehouse performance's quality due to customers' dissatisfaction of service. The order picking process is one of the main warehouse management strategies. With increase in the inventory of stored items and in the number of orders received, the picking process and the response time gain greater importance. Effective coordination between order batching and order picking process is of crucial role to enhance warehouse management system efficiency. In this paper, a novel Mixed Integer Nonlinear Programming (MINLP) model for on-line order batching is proposed for improving the warehouse performance, which in turn results in reducing the response and idle times. The proposed method is based on a blocked warehouse using a zoning system, which is called Online Order Batching in Blocked Warehouse with One Picker for each Block (OOBBWOPB). The mentioned model is solved by two algorithm of Artificial Bee-Colony Algorithm (ABC) and Ant-Colony Algorithm (ACO). Two numerical case studies are defined and analyzed in MATLAB software. Based on the results, the model shows better performance with a substantial reduction in the average customer orders response time compare to Zhang et al. (2017) results and the ACO yields better results than ABC.
International Journal of Production Economics, 1994
If the shop capacity is tight, it may not be possible to make a schedule that leads the completion times of all the parts processed in the shop to be exactly at their due dates. As a result, the shop may have to incur a holding cost for the parts finished earlier. This paper addresses a multi-due-date heterogeneous machine batch-scheduling problem to minimize the holding cost under the condition that parts to be processed should arrive at the production line just-in-time and that completed parts should be delivered just-in-time. The procedure to solve the problem is an algorithm that divides the whole planning horizon into a number of partitions of periods, distributes the parts to the partitions, distributes the resulting distributions to the available machines, and solves the problem of batch scheduling on each machine. Numerical experience showing the characteristics of the problem is also presented.
Development of an online order batching algorithm in blocked warehouse
Journal of Intelligent & Fuzzy Systems, 2019
The route length is taken by the operator is deemed to be an effective parameter in minimization of response time's orders in a typical warehouses with a manual picking system, in which the picker collects goods through depot. Therefore, reduction of the route length has been increasingly received considerable attention from the scholars in this area. The response time and system's costs are regarded as the most essential components necessitating the utilization of order batching process for rival companies, particularly when there is no information about time and amount of inbound orders, and even when there is substantial amounts of orders in large warehouses working with an online order entry system. This process has a profound impact on reducing the route length and thus decreasing the organization costs. Present study takes aim at investigation of order classification in the first time in the picker-to-part system as a manual picking system and an online order batching system, with the intent of minimizing the turnover time and idle time. Besides, an order batching model in a blocked warehouse using a zoning system is proposed which is called Online Order Batching in Blocked Warehouse with One Picker for each Block (OOBBWOPB). This is investigated by online order entry system using a nonlinear programming model based on meta-heuristic method of Teaching Learning Based Optimization (TLBO) algorithm. The average turnover time of the customer's orders is witnessed insignificant reduction using the proposed model, which lead to greatly enhance the total efficiency of warehouse system.
IIE Transactions, 1999
Raw material ordering policy and the manufacturing batch size for ®xed-interval deliveries of ®nished goods to multiple customers play a signi®cant role in economically managing the supply chain logistics. This paper develops an ordering policy for raw materials and determines an economic batch size for a product at a manufacturing center which supplies ®nished products to multiple customers, with a ®xed-quantity at a ®xed time-interval to each of the customers. In this model, an optimal multi-ordering policy for procurement of raw materials for a single manufacturing system is developed to minimize the total cost incurred due to raw materials and ®nished goods inventories. The carried over inventory of ®nished goods from the previous cycle is used as initial ®nished goods inventory, resulting in shifting the production schedule ahead for the next cycle. A closed-form solution to the problem is obtained for the minimal total cost. The algorithm is demonstrated for multiple customer systems.
This paper deals with the problem of preemptive scheduling in a two-stage supply chain framework. The supply chain environment contains two stages: production and transportation. In the production stage n jobs are processed on a manufacturer's bounded serial batching machine, preemptions are allowed, and set-up time is required before a new batch is processed. In the transportation stage each batch is delivered to a customer by a single vehicle. The objective is to minimize the makespan by making decisions for both mutually coordinated stages. Specifically, two versions are studied. The first one is that all jobs are available to be processed at time zero, and the second one is that jobs have different release times. An O(n log n) time algorithm is developed for the first version, and we show that it can produce the optimal schedule for the entire problem. For the second version, based on some useful properties we have designed an O(n log n) time heuristic and a novel lower bound. The worst-case performance ratio of our algorithm is bounded by 2. Our computational study with random instances of different scales shows high-quality solutions for either small-scale or large-scale instances returned in a reasonable PC times.
Performance analysis and design of batch ordering policies in supply chains
2007
Devising manufacturing/distribution strategies for supply chains and determining their parameter values have been challenging problems. Linking production management to stock keeping processes improves the planning of the supply chain activities, including material management, culminating in improved customer service levels. In this thesis, we investigate a multi-echelon supply chain consisting of a supplier, a plant, a distribution center and a retailer. Material flow between stages is driven by reorder point/order quantity inventory control policies. We develop a model to analyze supply chain behavior using some key performance metrics such as the time averages of inventory and backorder levels, as well as customer service levels at each echelon. The model is validated via simulation, yielding good agreement of robust performance metrics. The metrics are then used within an optimization framework to help design the supply chain by calculating optimal parameter values minimizing th...
Preemptive scheduling in a two-stage supply chain to minimize the makespan
This paper deals with the problem of preemptive scheduling in a two-stage supply chain framework. The supply chain environment contains two stages: production and transportation. In the production stage n jobs are processed on a manufacturer’s bounded serial batching machine, preemptions are allowed, and set-up time is required before a new batch is processed. In the transportation stage each batch is delivered to a customer by a single vehicle. The objective is to minimize the makespan by making decisions for both mutually coordinated stages. Specifically, two versions are studied. The first one is that all jobs are available to be processed at time zero, and the second one is that jobs have different release times. An O(n log n) time algorithm is developed for the first version, and we show that it can produce the optimal schedule for the entire problem. For the second version, based on some useful properties we have designed an O(n log n) time heuristic and a novel lower bound. The worst-case performance ratio of our algorithm is bounded by 2. Our computational study with random instances of different scales shows high-quality solutions for either small-scale or large-scale instances returned in a reasonable PC times. Keywords: batch scheduling; supply chain; preemption; transportation; release time; set-up time