The Single-Vendor Multibuyer Integrated Production-Delivery Model with Production Capacity under Stochastic Lead Time Demand

In this paper, we consider an integrated production-delivery model in which a vendor supplies the same product to multiple buyers. Unlike existing study, in this proposed model, we assume that the sum of all buyers’ demand rates is larger than the vendor’s production rate under normal work, but less...

Full description

Bibliographic Details
Main Author: Xuefang Sun
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2020/2309073
id doaj-8dbe0a33e72d4e01a5f6c1568fd02f69
record_format Article
spelling doaj-8dbe0a33e72d4e01a5f6c1568fd02f692020-11-25T02:06:20ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472020-01-01202010.1155/2020/23090732309073The Single-Vendor Multibuyer Integrated Production-Delivery Model with Production Capacity under Stochastic Lead Time DemandXuefang Sun0School of Economics and Management, Beihang University, Beijing 100191, ChinaIn this paper, we consider an integrated production-delivery model in which a vendor supplies the same product to multiple buyers. Unlike existing study, in this proposed model, we assume that the sum of all buyers’ demand rates is larger than the vendor’s production rate under normal work, but less than that under overtime. All buyers are independent of each other. For each buyer, the lead time demand is stochastic and the shortage during lead time is permitted. The main objective of this model is to determine the optimal production and delivery policies and the optimal overtime strategy, which minimize the joint expected annual cost of the system. Based on the genetic algorithm, we develop a solution procedure to find the optimal production, delivery, and overtime decision of this model. Computational experiments show the error rate between the objective values obtained by the proposed solution procedure and the solutions solved by the exhaustive method. The results indicate that the proposed mixed genetic algorithm is more effective and adoptable in comparison with the exhaustive method as it can be able to calculate the optimal solutions for at least 96% for the instances. Ultimately, an adequate numerical example is given to show the detailed process of the solution procedure, and sensitivity analysis of main parameters with managerial implication is discussed.http://dx.doi.org/10.1155/2020/2309073
collection DOAJ
language English
format Article
sources DOAJ
author Xuefang Sun
spellingShingle Xuefang Sun
The Single-Vendor Multibuyer Integrated Production-Delivery Model with Production Capacity under Stochastic Lead Time Demand
Mathematical Problems in Engineering
author_facet Xuefang Sun
author_sort Xuefang Sun
title The Single-Vendor Multibuyer Integrated Production-Delivery Model with Production Capacity under Stochastic Lead Time Demand
title_short The Single-Vendor Multibuyer Integrated Production-Delivery Model with Production Capacity under Stochastic Lead Time Demand
title_full The Single-Vendor Multibuyer Integrated Production-Delivery Model with Production Capacity under Stochastic Lead Time Demand
title_fullStr The Single-Vendor Multibuyer Integrated Production-Delivery Model with Production Capacity under Stochastic Lead Time Demand
title_full_unstemmed The Single-Vendor Multibuyer Integrated Production-Delivery Model with Production Capacity under Stochastic Lead Time Demand
title_sort single-vendor multibuyer integrated production-delivery model with production capacity under stochastic lead time demand
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2020-01-01
description In this paper, we consider an integrated production-delivery model in which a vendor supplies the same product to multiple buyers. Unlike existing study, in this proposed model, we assume that the sum of all buyers’ demand rates is larger than the vendor’s production rate under normal work, but less than that under overtime. All buyers are independent of each other. For each buyer, the lead time demand is stochastic and the shortage during lead time is permitted. The main objective of this model is to determine the optimal production and delivery policies and the optimal overtime strategy, which minimize the joint expected annual cost of the system. Based on the genetic algorithm, we develop a solution procedure to find the optimal production, delivery, and overtime decision of this model. Computational experiments show the error rate between the objective values obtained by the proposed solution procedure and the solutions solved by the exhaustive method. The results indicate that the proposed mixed genetic algorithm is more effective and adoptable in comparison with the exhaustive method as it can be able to calculate the optimal solutions for at least 96% for the instances. Ultimately, an adequate numerical example is given to show the detailed process of the solution procedure, and sensitivity analysis of main parameters with managerial implication is discussed.
url http://dx.doi.org/10.1155/2020/2309073
work_keys_str_mv AT xuefangsun thesinglevendormultibuyerintegratedproductiondeliverymodelwithproductioncapacityunderstochasticleadtimedemand
AT xuefangsun singlevendormultibuyerintegratedproductiondeliverymodelwithproductioncapacityunderstochasticleadtimedemand
_version_ 1715571569420402688