Weighted Tardiness Cost Research Articles

An integrated production and transportation scheduling problem with order acceptance and resource allocation decisions

In the global market competition, coordinating decisions and integrating different aspects of supply chains would help managers promote the overall performance of systems, and reduce the overall costs. The integration of production and transportation is one of the essential considerations of manufacturers to achieve more efficiency levels. In this paper, an integrated production and transportation scheduling problem is addressed. The objective is to maximize the revenue of accepted orders and to minimize the sum of delivery cost, weighted tardiness cost, and fixed cost of vehicles, by considering resource allocation and resource-dependent processing times. The problem is regarded as strong NP-Hard. A Mixed Integer Linear Programming (MILP) is proposed. Also, two meta-heuristic solution approaches, based on Adaptive Genetic Algorithm (AGA) and Tabu Search (TS) are proposed to solve this problem. The computational experiments based on small-scale and large-scale analyses are provided to assess the effects of different parameters of the problems on both optimality and solving time criteria. It is deduced that the proposed AGA has a better performance and higher efficiency, rather than the proposed TS, in terms of optimality. The results indicate the capability of the proposed algorithms in solving the real-life problems in an efficient manner.

A branch-price-and-cut algorithm for the vehicle routing problem with release and due dates

In this paper, we investigate the vehicle routing problem with release and due dates (VRPRD), which is a new variant of vehicle routing problem (VRP). In the problem, the order required by a customer is available for delivery later than its release date. A penalty cost, called tardiness cost, will be imposed if a customer is served after its due date. The objective of the VRPRD is to minimize the total routing and weighted tardiness costs. To address the problem, we develop an exact branch-price-and-cut algorithm based on the set-partitioning formulation. An effective bidirectional labeling algorithm is proposed to deal with the pricing problem. Numerical studies have verified that the proposed algorithm can obtain the exact optimal solutions for more than 75% of benchmark instances within approximately six minutes on average.

A multi-agent system for distributed maintenance scheduling

Due to the intrinsically geo-distributed subcontracting maintenance activity practice, the maintenance scheduling has for a long time been a major challenge in the industry. This research work presents a methodology to schedule the maintenance activities of geo-distributed assets. A multi-agent system based approach is proposed to enable the decision-making for the subcontractors in a distributed industrial environment under uncertainty. An auction based negotiation mechanism is designed to promote competition and cooperation among the different agents, and to obtain global good schedule.Compared to the Weighted Shortest Processing Time first–Heuristic–Earliest Due Date (WSPT-H-EDD) method, the experimental results show that the proposed approach is able to provide scheduling scheme with good performances in terms of Global Cost, Total Weighted Tardiness Cost and makespan.

Solving permutational routing problems by population-based metaheuristics

In this paper we consider two routing problems: traveling salesman problem (TSP, fundamental problem of the combinatorial optimization) and the TSP with times of traveling, times of processing and due dates where the objective is to minimize the total weighted tardiness (TSPTWT). Since problems are NP-hard in the strong sense, we propose a metaheuristic algorithm to determine a good sub-optimal solution. We present an algorithm based on the idea of researching and analyzing local optima. TSP with times of traveling, times of processing and due dates, and with the total weighted tardiness cost function is identical with the single machine total weighted tardiness problem with sequence-dependent setup times. It was possible to find the new best known solutions for 81 of 120 benchmark instances of this scheduling problem using the method proposed here.

Single machine rescheduling with new jobs arrivals and processing time compression

We consider job rescheduling problems where rescheduling is required in response to newly arriving jobs. To reduce the negative impacts of disruptions to the original schedule, the processing times of the newly arriving jobs can be reduced at a cost, which we call a time compression cost. The objective of the problem is to minimize total cost after rescheduling, which includes schedule disruption costs, time compression related costs, and a cost that depends on a traditional measure of schedule efficiency. We separately consider two different measures of schedule efficiency: total completion time and weighted tardiness, and present polynomial time algorithms for the total completion time case. For the weighted tardiness cost efficiency measure, we provide a heuristic based on very large scale neighborhood (VLSN) search.

Production and transport logistics scheduling with two transport mode choices

AbstractThis paper considers a new class of scheduling problems arising in logistics systems in which two different transportation modes are available at the stage of product delivery. The mode with the shorter transportation time charges a higher cost. Each job ordered by the customer is first processed in the manufacturing facility and then transported to the customer. There is a due date for each job to arrive to the customer. Our approach integrates the machine scheduling problem in the manufacturing stage with the transportation mode selection problem in the delivery stage to achieve the global maximum benefit. In addition to studying the NP‐hard special case in which no tardy job is allowed, we consider in detail the problem when minimizing the sum of the total transportation cost and the total weighted tardiness cost is the objective. We provide a branch and bound algorithm with two different lower bounds. The effectiveness of the two lower bounds is discussed and compared. We also provide a mathematical model that is solvable by CPLEX. Computational results show that our branch and bound algorithm is more efficient than CPLEX. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005

Reducing total tardiness cost in manufacturing cell scheduling by a multi-factor priority rule

Current literature about scheduling problems contains numerous studies on the use of dispatching rules with performance measures that are based only on time criteria. Various methods have been proposed to consider job processing time, job completion time, job due date, and combinations thereof. Considerations of tardiness cost, which offers a realistic reflection on the manufacturers' business concern, are usually ignored. One exception is the Weighted COVERT rule with the weighted tardiness cost concern. It has been tested and performs well in costbased performance. However, the performance of Weighted COVERT strongly depends upon the selected parameter values for estimating the expected waiting time of jobs. In this research, we present a multi-factor priority rule to improve the Weighted COVERT rule. Our new rule combines job processing time, job routing, job due date, and job-dependent tardiness cost for the scheduling in a manufacturing cell. The objective is to reduce the total tardiness cost. The central idea of this multi-factor priority rule is to give a higher priority to those jobs that have longer expected waiting time, shorter slack time, and higher ratio of tardiness cost over processing time. Performance comparisons (i.e. total tardiness cost, percentage of tardy jobs, and mean flow time) by simulation include five priority rules: SPT, EDD, Weighted COVERT, ATC, and our proposed multi-factor rule. The results have shown that the new rule is not only effective in reducing the total tardiness cost, but also performs well with respect to percentage of tardy jobs and mean flow time.

A decision theory based scheduling procedure for single-machine weighted earliness and tardiness problems

We consider the dynamic single-machine scheduling problem where the objective is to minimize the sum of weighted earliness and weighted tardiness costs. A single pass heuristic, based on decision theory, is developed for constructing schedules. The heuristic permits schedules with idle time between jobs and behaves like a dispatching procedure. The performance of the new heuristic is examined using 116 published problems for which the optimum solution is known. Its performance is also investigated using 540 randomly generated problems covering a variety of conditions by comparing it to two well known dispatching procedures, adapted for dynamic early/tardy problems. The results indicate that the heuristic performs very well.

Resource-constrained multi-project scheduling with tardy costs: Comparing myopic, bottleneck, and resource pricing heuristics

This paper addresses the problem of scheduling multiple resource-constrained projects with the objective of minimizing weighted tardiness costs. Extending our earlier heuristic scheduling work for production shops, we develop an efficient and effective means of generating low cost schedules for multiple projects requiring multiple resources. A ‘cost-benefit’ scheduling policy with resource pricing is developed which balances the marginal cost of delaying the start of an eligible activity with the marginal benefit of such a delay. A central part of this policy is the heuristic estimation of implicit resource prices, which form the basis for calculating marginal delay costs. The resulting policies are tested against a number of dispatch scheduling rules taken from the project scheduling literature, and against several new scheduling rules, with encouraging results for both the weighted tardiness problem and for the special case of weighted project delay.

Priority Rules for Job Shops with Weighted Tardiness Costs

Mainstream research in priority dispatching has considered jobs with equal delay penalties, thereby ruling out strategic differentiation of customer orders. We develop and test efficient dispatchin...

Priority Rules for Job Shops with Weighted Tardiness Costs

Mainstream research in priority dispatching has considered jobs with equal delay penalties, thereby ruling out strategic differentiation of customer orders. We develop and test efficient dispatching rules for the weighted tardiness problem with job-specific due dates and delay penalties. Our approach builds on previous greedy heuristics which assign the priority on the basis of the expected tardiness cost per immediate processing requirements. In multi-machine applications, estimates of the remaining leadtime are needed to determine local operation due dates and to evaluate the adequacy of the job's slack. Two slightly different “look-ahead” features are identified, and the corresponding priority rules are tested in job shop experiments with a variety of load conditions. The results indicate that the new rules are not only superior to competing rules for minimizing weighted tardiness penalties but are also robust for several other criteria, such as the number of tardy jobs and the costs of in-process inventories.