Common due date assignment scheduling for a no-wait flowshop with convex resource allocation and learning effect

This article addresses the no-wait flowshop scheduling problem with simultaneous consideration of common due date assignment, convex resource allocation and learning effect in a two machine setting. The processing time of each job can be controlled by its position in a sequence and also by allocating extra resource, which is a convex function of the amount of a common continuously divisible resource allocated to the job. The objective is to determine the optimal common due date, the resource allocation and the schedule of jobs such that the total earliness, tardiness and common due date cost (the total resource consumption cost) are minimized under the constraint condition that the total resource consumption cost (the total earliness, tardiness and common due date cost) is limited. Polynomial time algorithms are developed for two versions of the problem.     

A note on resource allocation scheduling with position-dependent workloads

In this note, single machine scheduling with concurrent resource allocation and position-dependent workloads is studied. The aim is to find jointly the optimal sequence and the optimal resource allocation. A bicriteria analysis of the problem is provided where the first criterion is to minimize the scheduling cost (i.e. makespan, total completion time, total absolute differences in completion times, total absolute differences in waiting times) and the second criterion is to minimize the total resource consumption cost. It is proved that four bicriteria problems can be solved efficiently.     

Bicriteria scheduling problems involving job rejection,controllable processing times and rate-modifying activity

This paper addresses the bicriteria scheduling problems with simultaneous consideration of job rejection, controllable processing times and rate-modifying activity on a single machine. A job is either rejected, in which case a rejection penalty will be incurred, or accepted and processed on the machine. The rate-modifying activity is an activity on the machine that changes the processing times of the jobs scheduled after the activity. The processing time of a job scheduled after the rate-modifying activity decreases with a job-dependent factor. The processing time of each job can also be controlled by allocating extra resource which is either a linear or a convex function of the amount of a common continuously divisible resource allocated to the job. The objective is to determine the rejected job set, the accepted job sequence, the time (location) of the rate-modifying activity and the resource allocation that jointly find the trade-off between two criteria, where the first criterion is measured as the sum of total completion time and resource consumption cost while the second criterion is the total rejection cost. We consider four different models for treating the two criteria. The computational complexity status and solution procedures are provided for the problems under consideration.     

Single machine due-window assignment scheduling with resource-dependent processing times to minimise total resource consumption cost

This paper considers a single-machine scheduling problem involving convex resource-dependent processing times and due-window assignment simultaneously. The goal is to minimise the total resource consumption cost under the constraint that the schedule cost involving earliness, tardiness, window location, window size and makespan does not exceed a given limit for two popular due window assignment methods: the common flow allowance (slack) due window assignment method (referred to SLKW) and the common due window assignment method (referred to CONW). We show that the problem can be solved in polynomial time. Some extensions of the problem are also given.     

Convex resource allocation scheduling in the no-wait flowshop with common flow allowance and learning effect

We study the problem of two-machine no-wait flowshop scheduling with learning effect and convex resource-dependent processing times. Under the condition of the due-date assignment with common flow allowance (i.e. slack (SLK) due-date assignment), we provide a bi-criteria analysis where the first criterion is to minimise the scheduling criteria (i.e. the weighted sum of earliness, tardiness and flow allowance costs), and the second criterion is to minimise the resource consumption cost (i.e. the weighted sum of resource consumption cost). The objective is to determine the optimal job sequence, resource allocations and common (flow allowance) slack time that minimise the three different versions of the two criteria. We prove that these problems can be solved in polynomial time.     

The optimal production and quality policy for the vendor in a trade

Arranging an inspection schedule for the production process and taking inspection and burn-in tests to screen out defective items in a production lot before items are shipped to the buyer are widely used by the vendor, such that the defective percentage in an outgoing batch satisfies the quality requirement specified in the contract between them. For an inspection schedule, the number of inspections and the length of time intervals between two inspections are influential to both the precision of detecting the manufacturing process and the inspection cost. As to the inspection test, it is not perfect, so there are two types of errors (Types I and II). Nevertheless, compared with inspection test, burn-in is usually costly. Hence, how to make a suitable trade-off between these three treatments (i.e., inspection schedule, inspection test, and burn-in test) such that the outgoing batch satisfies the purchaser's quality requirement with low cost is an important issue. The main purpose of this paper is to deal with the problem of determining the optimal inspection schedule and the optimal mixed policy of inspection and burn-in, where the average outgoing quality is used as the measure of quality. More specifically, by using the criterion of maximizing the expected profit that the vendor makes in a trade, a nonlinear programming problem is built to determine (a) the number of inspections undertaken in the production process, (b) the times at which the production process is inspected, (c) the total number of items that the vendor should produce (or the production run time), (d) the number of items for inspection, the number of items for burn-in, and the number of items that need neither inspection or burn-in, and (e) the optimal burn-in time for those needing burn-in testing. An example is provided to illustrate the proposed method.     

Construction Duration and Cost Simulation via Network-Program-Diagram

This paper outlines the creation of a simulation model used to extrapolate duration and resource requirements needed for the construction of bridges based on a sampling of data obtained during a field research conducted on the construction process of a single bridge. A sampling of statistical data was taken during a field investigation to measure schedule and resource requirements (labor, raw materials and machinery) at various stages of a bridge construction project. This data was used to identify the probability distribution and the associated parameters for the project examined, and a simulation model was built to extrapolate the necessary schedule and resource requirements needed for various stages of similar bridge projects based on Three-Point Estimation Method of Program Evaluation and Review Technique (PERT) and Monte Carlo Method. This simulation model’s resultant data for every process in an applicable construction project can be aggregated to form overall project duration and resource requirement statistical distribution using the Critical Path Method (CPM). The whole construction process will be visualized by a 4-dimensional (4D) model of the project which is created by appending time and resource requirements and to the 3-dimensional (3D) model that is built using the Building Information Modeling (BIM) and Alternativa 3D technology. Based on the simulation results of every procedure’s duration and resource requirements, the Network Program Diagram and Gantt Chart can be drawn with Flex and ActionScript language. Furthermore, with the Network Program Diagram at the core, the 4D model can incorporate simulation’s resultant data with respect to total time and cost of the project to show the condition of resource requirements and the project’s progressing at any time.     

Parallel-machine scheduling with controllable processing times and rate-modifying activities to minimise total cost involving total completion time and job compressions

In this paper, we consider unrelated parallel-machine scheduling involving controllable processing times and rate-modifying activities simultaneously. We assume that the actual processing time of a job can be compressed by allocating a greater amount of a common resource to process the job. We further assume that each machine may require a rate-modifying activity during the scheduling horizon. The objective is to determine the optimal job compressions, the optimal positions of the rate-modifying activities and the optimal schedule to minimise a total cost function that depends on the total completion time and total job compressions. If the number of machines is a given constant, we propose an efficient polynomial time algorithm to solve the problem.     

Integrated Project Scheduling and Material Planning with Variable Activity Duration and Rewards

Integrating project scheduling and material ordering adds more realism to project scheduling and considers additional trade-offs that could lead to reductions in the overall project cost. In this paper we review the evolution of the integrated problem, and investigate the impact of treating the activity duration as a decision variable on the activities schedule and materials plan. The effects of introducing rewards (penalties) for early (late) completion as well as materials quantity discounts on the project schedule and cost are also considered- These additions provide scheduling flexibility that might lead to further reduction in the project's total cost or makespan. Considering the various project costs, we found that there exists an optimal schedule that either starts as early as possible (ai time zero) or completes as late as possible. We also show that if the project starts at time zero, then its duration cannot be longer than that for the case where the schedule ends as late as possible. Ft is also shown that the material ordering policy does not follow the Wagner and Whitin model when activity duration is variable or in the presence of quantity discounts. These results have led to modeling and solving the problem in a more efficient manner. Extensive computational work shows the validity of the model and the solution approach.     

Distributed supply‐chain project rescheduling: Part I—impacts of information‐sharing strategies

A supply‐chain project normally involves a number of independent and autonomous enterprises that share information to varying levels. The initial project schedule (preschedule) established at the time of forming the supply‐chain often requires a series of amendments due to unexpected or abrupt disturbances such as temporary resource outage (e.g. machine break), arrival or cancellation of orders from customers, and change in an operation's processing time (e.g. rework). Rescheduling or adaptive scheduling is a process of updating/repairing the preschedule to adapt to the disturbances. Appropriate rescheduling methods must be chosen and applied depending on the specific protocol of sharing information agreed between the enterprises in the supply chain. This paper is concerned with the impacts of different levels of information sharing on the performance of supply‐chain project rescheduling problems. Three rescheduling methods are examined in the research. They are distributed AOR (Affected Operations Rescheduling), negotiation‐based rescheduling (NEG), and centralized total rescheduling (TR). These three rescheduling algorithms represent three typical information‐sharing scenarios: little information sharing, limited information sharing and complete information sharing, respectively. A comprehensive computational study is conducted under different experimental settings. The results show that NEG and distAOR outperforms the TR rescheduling in terms of total cost minimization and stability of schedule and contractual relationship. NEG is superior in both rescheduling efficiency and effectiveness due to the effect of a moderate level of information sharing.     

Minimising earliness and tardiness by integrating production scheduling with shipping information

Minimisation of earliness and tardiness is known to be critical to manufacturing companies because it may induce numerous tangible and intangible problems, i.e. extra storage cost, spacing, risk of damages, penalty, etc. In literature, earliness and tardiness is usually determined based on order due date, generally regarded as the time of delivering the finished products to the customers. In many papers, delivery time and cost required are usually simplified during the production scheduling. They usually assume that transportation is always available and unlimited. However, transportation usually constructs a critical portion of the total lead time and total cost in practice. Ignoring that will lead to an unreliable schedule. This is especially significant for electronic household appliances manufacturing companies as the studied company in this paper. In general, they usually rely on sea-freight transportation because of the economic reasons. As different sea-freight forwarders have different shipments to the same destination but with different shipping lead time, cost and available time. Adequately considering this shipping information with the production scheduling as an integrated model can minimise the costs induced by earliness and tardiness and the reliability of the schedule planned. In this paper, a two-level genetic algorithm (TLGA) is proposed, which is capable of simultaneously determining production schedule with shipping information. The optimisation reliability of the proposed TLGA is tested by comparing with a simple genetic algorithm. The results indicated that the proposed TLGA can obtain a better solution with lesser number of evolutions. In addition, a number of numerical experiments are carried out. The results demonstrate that the proposed integrated approach can reduce the tardiness, the storage cost, and shipping cost.     

Multi-objective optimization of a cooling tower assisted vapor compression refrigeration system

A cooling tower assisted vapor compression refrigeration machine has been considered for optimization with multiple criteria. Two objective functions including the total exergy destruction of the system (as a thermodynamic criterion) and the total product cost of the system (as an economic criterion), have been considered simultaneously. A thermodynamic model based on energy and exergy analyses and an economic model according to the Total Revenue Requirement (TRR) method have been developed. Three optimized systems including a single-objective thermodynamic optimized, a single-objective economic optimized and a multi-objective optimized are obtained. In the case of multi-objective optimization, an example of decision-making process for selection of the final solution from the Pareto frontier has been presented. The exergetic and economic results obtained for three optimized systems have been compared and discussed. The results have shown that the multi-objective design more acceptably satisfies generalized engineering criteria than other two single-objective optimized designs.     

Multiple Resource-Constrained Scheduling Using Branch and Bound

This paper focuses upon the problem of assigning feasible start times to a set of activities making up a project, static job shop, or static flowship type schedules under two constraint sets: (1) no activity may be started until all activities technologically established as its predecessor set have been completed, and (2) the total resource requirements of all activities in process at any time in the schedule must not exceed the level of availability for each of the multiple resource classes. The solution procedure used for these problems is branch and bound, and the resulting complete schedules are optimized with an objective of minimizing the completion time of the entire set of activities. Computational results on tests conducted on a number of randomly generated problem sets with up to 60 activities and six resource classes are presented.     

基于资源限制的多目标网络计划优化模型

目前网络计划优化研究要么没有考虑资源限定的柔性,要么只是集中于单纯的工期优化或资源优化等单目标优化。本文针对传统网络计划建模资源限制缺少柔性、优化目标单一等问题进行了深入的研究。在柔性资源的限制下,为使得工程网络计划达到总体最优,考虑工程项目的工期、成本、项目净现值、资源的均衡等多个目标,建立其网络计划优化模型,并采用粒子群算法予以求解。根据拓扑排序算法生成满足时序约束的活动序列并计算活动的时间参数。对于产生资源冲突的活动,依照执行优先权解决冲突资源的执行顺序,更新时间参数。采用随机权重的方法,让粒子群算法种群的多个个体进行随机转化,从而保持解的多样性。采用国际上通用的Patterson问题库中benchmark算例对本文提出的方法进行验证。结果表明,与初始方案相比,优化后的方案分别在工期上缩减了20%,成本上缩减了11.17%,净现值增加了11.82%,资源均衡度减少了18.29%。由此可见,提出的基于粒子群算法的优化模型对资源限制下的网络计划中的工期、成本、净现值、资源均衡度等多个目标均实现了不同程度的优化。     

Due-date assignment scheduling involving job-dependent learning effects and convex resource allocation

ABSTRACT

This article addresses single machine resource allocation scheduling problems with learning effects, where learning effects mean job-dependent position-based learning effects. For the common due-date assignment (CON) and slack due-date assignment (SLK) methods, a bi-cost analysis of the scheduling cost and the total weighted resource consumption cost is provided. The objective is to determine the optimal job sequence and the resource allocation simultaneously, such that the scheduling cost (the total weighted resource consumption cost) is minimized subject to the total weighted resource consumption cost (the scheduling cost) being limited. Solution procedures are provided for the problems under consideration.     

A robust scheduling for the multi-mode project scheduling problem with a given deadline under uncertainty of activity duration

The problem of this paper deals with the multi-mode project scheduling problem under uncertainty of activity duration where only the renewable resources are taken into account and a given deadline has to be met at the cost of recruiting additional resources. A heuristic algorithm is employed to solve this problem, and to maintain the robustness of the baseline schedule, the concept of critical chain project management (CCPM) is applied in which a new definition to resource buffer is considered. A simulation methodology is used to determine the size and location of resource buffers in the schedules in which three different buffer sizes and three different uncertainty levels are considered. Results and analysis of the simulation outcomes illustrate that resource buffers are useful and should be simulated by the CCPM schedules, as they help to decrease the total duration of the project during implementation and meet the deadline of the project with more assurance.     

Project scheduling algorithms for re-layout projects

The most common type of facility layout project is re-layout, which involves rearranging existing equipment in a facility. Project schedule development is an often overlooked yet critical portion of a facility re-layout project. When developing a re-layout project schedule, departments cannot be moved into their final locations until all previous occupants have moved. By incurring the cost of moving departments to temporary locations, it is possible to reduce the overall project duration. A two-criteria mixed-integer programming model is developed that finds the schedule minimizing department move costs subject to precedence constraints. An efficient algorithm uses this model to find all non-dominated time and cost solutions to the re-layout problem. Modifications to the basic model and algorithm handle resource constraints and turnaround space constraints. The algorithm and its modifications are demonstrated on an actual re-layout project.     

Project scheduling algorithms for re-layout projects

The most common type of facility layout project is re-layout, which involves rearranging existing equipment in a facility. Project schedule development is an often overlooked yet critical portion of a facility re-layout project. When developing a re-layout project schedule, departments cannot be moved into their final locations until all previous occupants have moved. By incurring the cost of moving departments to temporary locations, it is possible to reduce the overall project duration. A two-criteria mixed-integer programming model is developed that finds the schedule minimizing department move costs subject to precedence constraints. An efficient algorithm uses this model to find all non-dominated time and cost solutions to the re-layout problem. Modifications to the basic model and algorithm handle resource constraints and turnaround space constraints. The algorithm and its modifications are demonstrated on an actual re-layout project.     

Optimal periodic maintenance strategy under an intermittently used environment

In this paper, the optimal periodic replacement-like strategy with minimal repairs is considered under an intermittently used environment. Suppose that transactions or jobs with exponential service times arrive at a system according to a homogeneous Poisson process and the system is alternatively in either a busy or an idle period subject to demand for use. We derive approximately the optimal preventive maintenance schedule which minimizes the relevant expected cost criterion for the system which behaves intermittently on an M/M/1 queueing process, and compare it with the usual maintenance schedule for the continuously used system.     

An algorithm for scheduling parallel processors

This paper deals with optimal scheduling of jobs on identical parallel processors. The paper develops an algorithm for determining the optimal schedule and gives a proof of the algorithm. The criterion used is that of minimizing the total cost for processing all jobs when the jobs are assigned non-decreasing waiting costs which are non-linear. Extension of the algorithm for jobs with due dates is also given. Computational results are given which indicate the effectiveness of the algorithm as compared to complete enumeration.