Supply Chain Scheduling with Transportation Cost on a Single Machine

2011 ◽  
Vol 382 ◽  
pp. 106-109
Author(s):  
Jing Fan

Supply chain scheduling problem is raised from modern manufacturing system integration, in which manufacturers not only process orders but also transport products to customer’s location. Therefore, the system ought to consider how to appropriately send finished jobs in batches to reduce transportation costs while considering the processing sequence of jobs to reduce production cost. This paper studies such a supply chain scheduling problem that one manufacturer produces with a single machine and deliveries jobs within limited transportation times to one customer. The objective function is to minimize the total sum of production cost and transportation cost. The NP hard property of the problem is proved in the simpler way, and the pseudo-dynamic programming algorithm in the literature is modified as the MDP algorithm to get the optimal solution which is associated with the total processing times of jobs.

2016 ◽  
Vol 2016 ◽  
pp. 1-9
Author(s):  
Farhad Ghassemi Tari

The problem of allocating different types of vehicles for transporting a set of products from a manufacturer to its depots/cross docks, in an existing transportation network, to minimize the total transportation costs, is considered. The distribution network involves a heterogeneous fleet of vehicles, with a variable transportation cost and a fixed cost in which a discount mechanism is applied on the fixed part of the transportation costs. It is assumed that the number of available vehicles is limited for some types. A mathematical programming model in the form of the discrete nonlinear optimization model is proposed. A hybrid dynamic programming algorithm is developed for finding the optimal solution. To increase the computational efficiency of the solution algorithm, several concepts and routines, such as the imbedded state routine, surrogate constraint concept, and bounding schemes, are incorporated in the dynamic programming algorithm. A real world case problem is selected and solved by the proposed solution algorithm, and the optimal solution is obtained.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yuncheng Luo

In this paper, we investigate a static stochastic single machine JIT scheduling problem in which the jobs’ processing times are stochastically independent and follow geometric distributions whose mean is provided, due dates are geometrically distributed with a common mean, and both the unit penalty of earliness/tardiness and the fixed penalty of earliness/tardiness are deterministic and different. The objective is to minimize the expected total penalties for quadratic earliness, quadratic tardiness, and early and tardy jobs. We prove that the optimal schedule to minimize this problem is V-shaped with respect to the ratio of mean processing time to unit tardiness penalty under the specific condition. Also, we show a special case and two theorems related to this JIT scheduling problem under specific situations where the optimal solutions exist. Finally, based on the V-shaped characteristic, a dynamic programming algorithm is designed to achieve an optimal V-shaped schedule in pseudopolynomial time.


Author(s):  
Ali Skaf ◽  
Sid Lamrous ◽  
Zakaria Hammoudan ◽  
Marie-Ange Manier

The quay crane scheduling problem (QCSP) is a global problem and all ports around the world seek to solve it, to get an acceptable time of unloading containers from the vessels or loading containers to the vessels and therefore reducing the docking time in the terminal. This paper proposes three solutions for the QCSP in port of Tripoli-Lebanon, two exact methods which are the mixed integer linear programming and the dynamic programming algorithm, to obtain the optimal solution and one heuristic method which is the genetic algorithm, to obtain near optimal solution within an acceptable CPU time. The main objective of these methods is to minimize the unloading or the loading time of the containers and therefore reduce the waiting time of the vessels in the terminals. We tested and validated our methods for small and large random instances. Finally, we compared the results obtained with these methods for some real instances in the port of Tripoli-Lebanon.


Kybernetes ◽  
2018 ◽  
Vol 47 (7) ◽  
pp. 1401-1419 ◽  
Author(s):  
Ali Borumand ◽  
Mohammad Ali Beheshtinia

Purpose Proper management of supplies and their delivery greatly affects the competitiveness of companies. This paper aims to propose an integrated decision-making approach for integrated transportation and production scheduling problem in a two-stage supply chain. The objective functions are minimizing the total delivery tardiness, production cost and the emission by suppliers and vehicles and maximizing the production quality. Design/methodology/approach First, the mathematical model of the problem is presented. Consequently, a new algorithm based on a combination of the genetic algorithm (GA) and the VIKOR method in multi-criteria decision-making, named GA-VIKOR, is introduced. To evaluate the efficiency of GA-VIKOR, it is implemented in a pharmaceutical distribution company located in Iran and the results are compared with those obtained by the previous decision-making process. The results are also compared with a similar algorithm which does not use the VIKOR method and other algorithm mentioned in the literature. Finally, the results are compared with the optimized solutions for small-sized problems. Findings Results indicate the high efficiency of GA-VIKOR in making decisions regarding integrated production supply chain and transportation scheduling. Research limitations/implications This research aids the manufacturers to minimize their total delivery tardiness and production cost and at the same time maximize their production quality. These improve the customer satisfaction as a part of social and manufacturer’s power of competitiveness. Furthermore, the emission minimizing objective functions directly provides benefits to the environment and the society. Originality/value This paper investigates a new supply chain scheduling the problems and presents its mathematical formulation. Moreover, a new algorithm is introduced to solve the multi-objective problems.


2011 ◽  
Vol 341-342 ◽  
pp. 369-373
Author(s):  
He Ping Zhang

With the rapid development of the global economy, more and more enterprises emphasize on the coordination with the partners to improve the supply chain competitive capability. This paper focuses on the united scheduling of the three-layer supply chain and the coordination mechanisms of agile supply chain. The objective is to minimize the total transportation cost and improve the customer’s service level, which is achieved by scheduling the jobs and delivering them to the next stage in batches. Based on the features of the optimal scheduling, a dynamic programming algorithm is proposed.


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