Minimizing Flow Time Research Articles

Multi-objective simulation optimization for uncertain resource assignment and job sequence in automated flexible job shop

In this study a multi-objective problem considering uncertainty and flexibility of job sequence in an automated flexible job shop (AFJS) is considered using manufacturing simulation. The AFJS production system is considered as a complex problem due to automatic elements requiring planning and optimization. Several solution approaches are proposed lately in different categories of meta-heuristics, combinatorial optimization and mathematically originated methods. This paper provides the metamodel using simulation optimization approach based on multi-objective efficiency. The proposed metamodel includes different general techniques and swarm intelligent technique to reach the optimum solution of uncertain resource assignment and job sequences in an AFJS. In order to show the efficiency and productivity of the proposed approach, various experimental scenarios are considered. Results show the optimal resources assignment and optimal job sequence which cause efficiency and productivity maximization. The makespan, number of late jobs, total flow time and total weighted flow time minimization have been resulted in an automated flexible job shop too.

An iterated greedy algorithm for total flow time minimization in unrelated parallel batch machines with unequal job release times

This paper investigates the problem of scheduling a set of jobs with arbitrary sizes and non-zero release times on a set of unrelated parallel batch machines with different capacities so as to minimize the total flow time of the jobs. The total flow time, defined as the total amount of time that the jobs spend in the system (i.e. the period between the job release dates and its completion times), is one of the most important objectives in scheduling problems, since it can lead to stable utilization of resources and reduction of working-in-process inventory. Motivated by the computational complexity of the problem, a simple and effective iterated greedy (IG) algorithm is proposed to solve it. The IG algorithm uses an efficient greedy heuristic to reconstruct solutions and a local search procedure to further enhance the solution quality. In attempting to obtain optimal solutions for small-medium size instances, a mixed integer programming model for the problem is also presented. The performance of the proposed algorithm is tested on a comprehensive set of small, medium and large benchmark of randomly generated instances, and is compared to three benchmark meta-heuristic algorithms (Discrete Differential Evolution, Ant Colony Optimization and Simulated Annealing) recently proposed for similar parallel batch machine scheduling problems. Experimental results and statistical tests show that the proposed algorithm is significantly superior in performance than the other algorithms.

Production orders planning using additional backward pass scheduling approach

The paper focuses on the scheduling problem of minimizing flow time of production orders in job shop class systems. The proposed method supports both forward and backward scheduling and use additional backward pass for calculating the latest possible release date of a given production order. Depending on the adopted strategy, two or three stages are implemented in which the new due date and new release date is searched successively for each production order. Application of this approach causes that the scheduling of any order can be realized according to one of five ways. Four decision steps associated with the choice of the right method of order scheduling were distinguished. Examples illustrating the application of the proposed approach for the case of the forward and backward base strategy were also presented.

Incorporating preventive maintenance into the m-machine no-wait flow-shop scheduling problem with total flow-time minimization: a computational study

ABSTRACTIn this article, the impact of preventive maintenance policies on the constructive heuristics performance for the no-wait flow-shop problem with total flow-time minimization is evaluated. The main constructive heuristics for the m-machine no-wait flow-shop scheduling problem with total flow-time minimization are compared through computational experiments with a set of 5760 problems. The results show that the adopted parameters significantly affect the performance of the constructive heuristics; also, the computational effort required to solve the problems increases owing to the complexity of the function-objective calculation. Heuristics proposed by Laha and Sapkal (LSH) and Framinan, Nagano and Moccellin (FNMH) provide the best solutions for both evaluated policies.

Um estudo computacional de novas regras de prioridade para flow shop com tempos de setup e diferentes datas de liberação

Este trabalho aborda o sistema de produção flow shop com tempos de setup independentes da sequência, tarefas com diferentes instantes de liberação e dois problemas distintos: minimização da duração total da programação (makespan) e do tempo médio de fluxo (flowtime). Foi empreendido um amplo estudo computacional do desempenho de novas regras de prioridade, muito utilizadas na prática pelas empresas, aqui definidas com base na estrutura dos problemas analisados. Conforme é bem conhecido, a eficiência computacional das regras de prioridade como métodos de solução já é presumida. Portanto, nesta pesquisa focou-se na análise da eficácia, ou seja, da qualidade da solução atingida pela aplicação de tais regras nos dois problemas considerados. Os resultados provaram a aplicabilidade dos métodos propostos e identificaram as melhores regras para cada caso, com seus respectivos critérios de ordenação.

Fleet Sizing of Automated Material Handling Using Simulation Approach

Automated material handling tends to be chosen rather than using human power in material handling activity for production floor in manufacturing company. One critical issue in implementing automated material handling is designing phase to ensure that material handling activity more efficient in term of cost spending. Fleet sizing become one of the topic in designing phase. In this research, simulation approach is being used to solve fleet sizing problem in flow shop production to ensure optimum situation. Optimum situation in this research means minimum flow time and maximum capacity in production floor. Simulation approach is being used because flow shop can be modelled into queuing network and inter-arrival time is not following exponential distribution. Therefore, contribution of this research is solving fleet sizing problem with multi objectives in flow shop production using simulation approach with ARENA Software

Multi-Objective Parallel Variable Neighborhood Search for Energy Consumption Scheduling in Blocking Flow Shops

Blocking flow shop scheduling problem has been extensively studied because of its widespread industrial applications. However, the existing research mostly aims at makespan or total flow time minimization and ignores the criterion for energy saving. This paper investigates the blocking flow shop scheduling problem with both makespan and energy consumption criteria. First, the multi-objective model of blocking flow shop scheduling is formulated in consideration of machine energy consumed in blocking and idle time. Then, a multi-objective parallel variable neighborhood search (MPVNS) algorithm is proposed to solve this problem. An improved Nawaz–Enscore–Ham-based heuristic is developed to generate initial solutions, and a variable neighborhood search is designed to explore these solutions in parallel. Furthermore, an insertion-based pareto local search method is embedded to enhance the exploitation of the algorithm. Finally, in order to validate its effectiveness, the MPVNS is compare with other two effective multi-objective metaheuristics by computational experiments based on well-known benchmark instances. The experimental results illustrate that the proposed algorithm is superior to non-dominated sorting genetic algorithm (II) and bi-objective multi-start simulated annealing algorithm in terms of set coverage and hypervolume measures.

Minimum Flow Time in a Tandem Two-Server Fluid Network

We consider a tandem two-server fluid network with two fluid types. Each server in the network has two buffers, one for each fluid, and the capacity of each server can be shared among the fluids. An initial amount of fluids is to be processed by both servers and drained through the system. We determine the processing rates for which the servers' capacity is optimally shared, with the objective of minimizing the total flow time. Three cases of the optimal strategy are discussed.

A beam-search-based constructive heuristic for the PFSP to minimise total flowtime

In this paper we present a beam-search-based constructive heuristic to solve the permutation flowshop scheduling problem with total flowtime minimisation as objective. This well-known problem is NP-hard, and several heuristics have been developed in the literature. The proposed algorithm is inspired in the logic of the beam search, although it remains a fast constructive heuristic.The results obtained by the proposed algorithm outperform those obtained by other constructive heuristics in the literature for the problem, thus modifying substantially the state-of-the-art of efficient approximate procedures for the problem. In addition, the proposed algorithm even outperforms two of the best metaheuristics for many instances of the problem, using much lesser computation effort. The excellent performance of the proposal is also proved by the fact that the new heuristic found new best upper bounds for 35 of the 120 instances in Taillard’s benchmark.

Temperature aware online algorithms for minimizing flow time

We consider the problem of minimizing the total flow time of a set of unit sized jobs in a discrete time model, subject to a temperature threshold. Each job has its release time and its heat contribution. At each time step the temperature of the processor is determined by its temperature at the previous time step, the job scheduled at this time step and a cooling factor. We show a number of lower bound results, including the case when the heat contributions of jobs are only marginally larger than a trivial threshold. Then we consider a form of resource augmentation by giving the online algorithm a higher temperature threshold, and show that the Hottest First algorithm can be made 1-competitive, while other common algorithms like Coolest First cannot. Finally we give some results in the offline case.

Minimizing the maximum flow time in batch scheduling

We consider the maximum flow time minimization problem in batch scheduling, which is a capacitated version of broadcast scheduling. In this setting, n different pages of information are available at the server which receives requests from clients over time for specific pages. The server can transmit at most one page p at each time to satisfy a batch of requests for the same page p, up to a certain capacity Bp. In this paper we give the first (1+ϵ)-approximations for this problem with arbitrarily small resource augmentation, using either more capacity or more speed.

An effective constructive heuristic for permutation flow shop scheduling problem with total flow time criterion

This article addresses the permutation flow-shop scheduling problem with total flow time minimization criterion. The problem is proved to be NP-hard; thus, the development of heuristic methods that provide high-quality solutions with computational efficiency are the motivating aspects for the development of this research. In this article, a new simple constructive heuristic method has been proposed to solve the problem. Initially, an extensive literature review with key methods was performed for analysis, comparison, and evaluation. Then, a new simple heuristic method has been proposed and evaluated by means of extensive computational experiments. The results showed that the proposed method provides high-quality solutions with computational efficiency, significantly outperforming the best simple heuristics found in the literature.

Scheduling products with subassemblies and changeover time

We revisit the problem, previously studied by Coffman et al, of scheduling products with two subassemblies on a common resource, where changeovers consume time, under the objective of flow-time minimization. We derive some previously unidentified structural properties that could be important to researchers working on similar batch scheduling problems. We show that there exists a series of base schedules from which optimal schedules can be easily derived. As these base schedules build on each other, they are easy to construct as well. We also show that the structure of these base schedules is such that batch sizes decrease over time in a well-defined manner. These insights about the general form of the schedules might also be important to practitioners wanting some intuition about the schedule structure that they are implementing.

A computational evaluation of constructive and improvement heuristics for the blocking flow shop to minimise total flowtime

This paper focuses on the blocking flow shop scheduling problem with the objective of total flowtime minimisation. This problem assumes that there are no buffers between machines and, due to its application to many manufacturing sectors, it is receiving a growing attention by researchers during the last years. Since the problem is NP-hard, a large number of heuristics have been proposed to provide good solutions with reasonable computational times. In this paper, we conduct a comprehensive evaluation of the available heuristics for the problem and for related problems, resulting in the implementation and testing of a total of 35 heuristics. Furthermore, we propose an efficient constructive heuristic which successfully combines a pool of partial sequences in parallel, using a beam-search-based approach. The computational experiments show the excellent performance of the proposed heuristic as compared to the best-so-far algorithms for the problem, both in terms of quality of the solutions and of computational requirements. In fact, despite being a relative fast constructive heuristic, new best upper bounds have been found for more than 27% of Taillard’s instances.

Multi-Agent Path Finding with Payload Transfers and the Package-Exchange Robot-Routing Problem

We study transportation problems where robots have to deliver packages and can transfer the packages among each other. Specifically, we study the package-exchange robot-routing problem (PERR), where each robot carries one package, any two robots in adjacent locations can exchange their packages, and each package needs to be delivered to a given destination. We prove that exchange operations make all PERR instances solvable. Yet, we also show that PERR is NP-hard to approximate within any factor less than 4/3 for makespan minimization and is NP-hard to solve for flowtime minimization, even when there are only two types of packages. Our proof techniques also generate new insights into other transportation problems, for example, into the hardness of approximating optimal solutions to the standard multi-agent path-finding problem (MAPF). Finally, we present optimal and suboptimal PERR solvers that are inspired by MAPF solvers, namely a flow-based ILP formulation and an adaptation of conflict-based search. Our empirical results demonstrate that these solvers scale well and that PERR instances often have smaller makespans and flowtimes than the corresponding MAPF instances.

Fast local neighborhood search algorithm for the no-wait flow shop scheduling with total flow time minimization

A fast local neighbourhood search (FLNS) algorithm is proposed in this paper to minimise the total flow time in the no-wait flow shop scheduling problem, which is known to be NP-hard for more than two machines. In this work, an unscheduled job sequence is constructed firstly according to the total processing time and standard deviation of jobs on the machines. This job sequence is undergone an initial optimisation using basic neighbourhood search algorithm. Then, an innovative local neighbourhood search scheme is designed to search for the partial neighbourhood in each iterative processing and calculate the neighbourhood solution with an objective increment method. This not only improves the solution quality significantly, but also speeds up the convergence of the solution of the algorithm. Moreover, a probabilistic acceptance criterion is adopted to help our method escape from the local optima. Based on Taillard’s benchmarks, the experimental results show that the proposed FLNS algorithm is superior to major existing algorithms (IHA, IBHLS, GA-VNS and DHS) in terms of both quality and robustness, and can provide best upper bounds. The in-depth statistical analysis demonstrates that the promising performance of our proposed algorithm is also statistically significant.

Efficient heuristic algorithms for the blocking flow shop scheduling problem with total flow time minimization

This paper proposes two constructive heuristics, i.e. HPF1 and HPF2, for the blocking flow shop problem in order to minimize the total flow time. They differ mainly in the criterion used to select the first job in the sequence since, as it is shown, its contribution to the total flow time is not negligible. Both procedures were combined with the insertion phase of NEH to improve the sequence. However, as the insertion procedure does not always improve the solution, in the resulting heuristics, named NHPF1 and NHPF2, the sequence was evaluated before and after the insertion to keep the best of both solutions. The structure of these heuristics was used in Greedy Randomized Adaptive Search Procedures (GRASP) with variable neighborhood search in the improvement phase to generate greedy randomized solutions. The performance of the constructive heuristics and of the proposed GRASPs was evaluated against other heuristics from the literature. Our computational analysis showed that the presented heuristics are very competitive and able to improve 68 out of 120 best known solutions of Taillard’s instances for the blocking flow shop scheduling problem with the total flow time criterion.

An efficient Discrete Artificial Bee Colony algorithm for the blocking flow shop problem with total flowtime minimization

This paper presents a high performing Discrete Artificial Bee Colony algorithm for the blocking flow shop problem with flow time criterion. To develop the proposed algorithm, we considered four strategies for the food source phase and two strategies for each of the three remaining phases (employed bees, onlookers and scouts). One of the strategies tested in the food source phase and one implemented in the employed bees phase are new. Both have been proved to be very effective for the problem at hand. The initialization scheme named HPF2(λ,μ) in particular, which is used to construct the initial food sources, is shown in the computational evaluation to be one of the main procedures that allow the DABC_RCT to obtain good solutions for this problem. To find the best configuration of the algorithm, we used design of experiments (DOE). This technique has been used extensively in the literature to calibrate the parameters of the algorithms but not to select its configuration. Comparing it with other algorithms proposed for this problem in the literature demonstrates the effectiveness and superiority of the DABC_RCT.

Constructal design for a disc-shaped area based on minimum flow time of a flow system

Based on constructal theory, a model of a “disc-point” flow system with various flow speeds is considered in this paper. The optimal constructs of the radial-pattern and first order branched-pattern discs are obtained by taking the minimum maximum flow time and minimum average flow time as optimization objectives, respectively. The results show that there exist an optimal aspect ratio of the elemental sector and an optimal elemental fraction of the high speed flow channel which lead to the minimizations of the maximum flow time and average flow time of the flow system, respectively. The optimal constructs based on these two objectives are different. When the first order fraction is 0.1 and the number of elemental tributaries is 2, the dimensionless critical radius, which determine whether the radial-pattern design or branched-pattern design for the high speed flow channels is adopted, is 3.02 for minimum maximum flow time objective and is 2.29 for minimum average flow time objective. There exists an optimal number of the elemental tributaries which leads to the double minimum dimensionless average flow time of the flow system. The constructal optimization of the flow system by taking minimum flow time as optimization objective is helpful to improve its transfer performance.

Comparison of Density Tests for Thin Hot-Mix Asphalt Overlays

The thin overlay mix (TOM) and ultrathin overlay mix (UTOM) specifications in Texas test falling head water flow as a surrogate measure of density. Current flow time criterion has never been correlated to density; furthermore, there is no maximum flow time to prevent overcompaction. A rolling density meter (radar) and a circular track meter may also be used to measure thin lift density. These tests and traditional core testing were used on three projects, and the correlations between tests were analyzed. Correlations were strong on a project-by-project basis but generally poor when data sets were combined. Flow time and mean profile depth, flow time and core voids, and surface dielectric and core voids were the strongest correlations overall; measured voids were unusually high. The reliability of taking core measurements on such thin samples is questionable and may be overly influenced by the surface texture. The flow test should continue to be used as a surrogate measure of density. No minimum flow time was recommended because of unusually high void measurements. To avoid overcompaction in TOMs, flow time should be less than 6 min on higher-speed or critical sections and less than 10 min on lower-speed, noncritical sections. From the standpoint of macrotexture in the UTOM, no upper limit is recommended for flow time. The rolling density meter should be employed on project-specific issues when full-coverage density measurements are desired. Further testing should be conducted on the reliability of measuring voids on very thin cores.