Considering the characteristics of time-of-use tariffs and multi-shifts in real-life project execution scenarios, we present a multi-mode resource-constrained project scheduling problem with multi-shift and time-of-us...
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Considering the characteristics of time-of-use tariffs and multi-shifts in real-life project execution scenarios, we present a multi-mode resource-constrained project scheduling problem with multi-shift and time-of-use tariffs (MRCPSP-MS-TOU). The MRCPSP-MS-TOU is a bi-objective scheduling problem that aims to simultaneously minimise both project duration and energy costs. In this problem, renewable resources are the critical equipment that consumes the most energy and can work continuously for multiple shifts. Activities that require critical equipment with high energy consumption are given priority for shifts with lower electricity prices under time-of-use tariffs. We construct a mixed integer linear programming model for the MRCPSP-MS-TOU. For small-scale projects, the epsilon-constraint method is implemented to solve the MRCPSP-MS-TOU using the Gurobi optimiser. For large-scale projects, this paper develops meta-heuristic algorithms in the framework of the two non-dominated sorting genetic algorithm versions. The MRCPSP-MS-TOU enables manufacturers and the construction industry to schedule projects using time-of-use tariffs and multi-shifts in a more efficient manner since it can control the intensity of energy consumption, reduce project costs, make full use of energy-intensive equipment, and effectively reduce order delivery time.
projectscheduling is a vital management task in many organizations across various industries. A project typically consists of activities that require time and scarce resources for execution. In many projects, there a...
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projectscheduling is a vital management task in many organizations across various industries. A project typically consists of activities that require time and scarce resources for execution. In many projects, there are trade-offs between the resource requirements and the duration of activities. These trade-offs can be represented via multiple execution modes of activities, which are considered in the multi-mode resource-constrained project scheduling problem (MRCPSP). The MRCPSP comprises determining the activities' start times and execution modes to minimize the project completion time while respecting precedence relations and availabilities of renewable and nonrenewable resources. In this paper, we propose several discrete-time (DT) and one continuous-time (CT) mixed-integer linear programming (MILP) model for the MRCPSP based on models for the single-moderesource-constrainedprojectscheduling problem (RCPSP). We first analyze the models' LP relaxations and show an equivalence between DT models. Then, we compare the computational performance of the models on benchmark instances. Our results indicate that the proposed CT model outperforms the state-of-the-art models on large problem instances and problem instances with relatively long activity durations, while it is competitive on smaller problem instances. A possible explanation for this outperformance is that the LP relaxations of the proposed CT model can be solved considerably faster than the LP relaxations of the state-of-the-art models.
This paper proposes to consider alternative project structures when dealing with the multi-moderesourceconstrainedprojectscheduling problem. An AND-OR network is used to present this alternative project structures...
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This paper proposes to consider alternative project structures when dealing with the multi-moderesourceconstrainedprojectscheduling problem. An AND-OR network is used to present this alternative project structures innovatively. The problem is formulated as a bi-objective linear integer program, which minimizes the makespan and total cost. A hybrid metaheuristic is developed based on AND-OR network to solve this NP-hard problem efficiently, which nests adapted Tabu Search (outer layer) and NSGA-II algorithm (inner layer). A large amount of computational experiments of different sizes are conducted, and compared with solutions generated by CPLEX, traditional Tabu Search, enumeration-based method and single-layer NSGA-II. The experimental results show the advantages of the proposed model and method, especially with large-size problems.
In this paper, an effective shuffled frog-leaping algorithm (SFLA) is proposed for solving the multi-mode resource-constrained project scheduling problem (MRCPSP). In the SFLA, the virtual frogs are encoded as the ext...
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In this paper, an effective shuffled frog-leaping algorithm (SFLA) is proposed for solving the multi-mode resource-constrained project scheduling problem (MRCPSP). In the SFLA, the virtual frogs are encoded as the extended multi-mode activity list (EMAL) and decoded by the multi-mode serial schedule generation scheme (MSSGS). Initially, the mode assignment lists of the population are generated randomly, and the activity lists of the population are generated by the regret-based sampling method and the latest finish time (LFT) priority rule. Then, virtual frogs are partitioned into several memeplexes that evolve simultaneously by performing the simplified two-point crossover (STPC). To enhance the exploitation ability, the combined local search including the multi-mode permutation based local search (MPBLS) and the multi-mode forward-backward improvement (MFBI) is further performed in each memeplex. To maintain the diversity of each memeplex, virtual frogs are periodically shuffled and reorganized into new memeplexes. Computational results based on the well-known benchmarks and comparisons with some existing algorithms demonstrate the effectiveness of the proposed SFLA. (C) 2011 Elsevier Inc. All rights reserved.
In the multi-mode resource-constrained project scheduling problem, a set of precedence-related project activities and, for each activity, a set of alternative execution modes are given. Each activity requires some tim...
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In the multi-mode resource-constrained project scheduling problem, a set of precedence-related project activities and, for each activity, a set of alternative execution modes are given. Each activity requires some time and some scarce resources during execution;these requirements depend on the selected execution mode. Sought is a project schedule, i.e, a start time and an execution mode for each activity, such that the project makespan is minimized. In the literature, besides a large variety of specific solution approaches, several Mixed-Integer Linear Programming (MILP) models have been proposed for this problem. We present two novel MILP models that are based on mode-selection, resource-assignment and sequencing variables;we enhance the performance of the models by eliminating some symmetric solutions from the search space and by adding some redundant sequencing constraints for pairs and for triples of activities that cannot be processed in parallel. In a comparison with reference models from the literature, it turned out that the advantages of the novel models are a simple structure, an enhanced flexibility, and a superior performance when the range of the activities' durations is relatively large.
In this paper, we address the waterway ship scheduling problem (WSSP), which finds applications in the management of ship arrivals and departures at maritime ports near channels and waterways. It incorporates practica...
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In this paper, we address the waterway ship scheduling problem (WSSP), which finds applications in the management of ship arrivals and departures at maritime ports near channels and waterways. It incorporates practically relevant conflicts which stem from tidal changes, curfews, ship properties or traffic. We propose a reformulation of the WSSP as a variant of the multi-mode resource-constrained project scheduling problem, which incorporates time-dependent resource capacities besides earliest and latest start times for the tasks. This problem is solved through integer programming, using a compact mathematical formulation. Our approach outperforms previous methods by solving all the existing literature instances to optimality. Most of them are solved at the root node within less than 2s.
In this paper, an estimation of distribution algorithm (EDA) is proposed to solve the multi-mode resource-constrained project scheduling problem (MRCPSP). In the EDA, the individuals are encoded based on the activity-...
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In this paper, an estimation of distribution algorithm (EDA) is proposed to solve the multi-mode resource-constrained project scheduling problem (MRCPSP). In the EDA, the individuals are encoded based on the activity-mode list (AML) and decoded by the multi-mode serial schedule generation scheme (MSSGS), and a novel probability model and an updating mechanism are proposed for well sampling the promising searching region. To further improve the searching quality, a multi-mode forward backward iteration (MFBI) and a multi-mode permutation based local search method (MPBLS) are proposed and incorporated into the EDA based search framework to enhance the exploitation ability. Based on the design-of-experiment (DOE) test, suitable parameter combinations are determined and some guidelines are provided to set the parameters. Simulation results based on a set of benchmarks and comparisons with some existing algorithms demonstrate the effectiveness of the proposed EDA. (C) 2011 Elsevier Ltd. All rights reserved.
This paper presents results from an extensive computational study of the multi-moderesource-con strained projectscheduling problem when activities can be split during scheduling under situations where resources may ...
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This paper presents results from an extensive computational study of the multi-moderesource-con strained projectscheduling problem when activities can be split during scheduling under situations where resources may be temporarily not available. All resources considered are renewable and each resource unit may not be available at all times due to resource vacations, which are known in advance, and assignment to other finite duration activities. A designed experiment is conducted that investigates project makespan improvement when activity splitting is permitted in various project scenarios, where different project scenarios are defined by parameters that have been used in the research literature. A branch-and-bound procedure is applied to solve a number of small projectscheduling problems with and without activity splitting. The results show that, in the presence of resource vacations and temporary resource unavailability, activity splitting can significantly improve the optimal project makespan in many scenarios, and that the makespan improvement is primarily dependent on those parameters that impact resource utilization. (c) 2005 Elsevier B.V. All rights reserved.
The multi-mode resource-constrained project scheduling problem with minimum and maximum time lags is considered in the paper. An activity is performed in a mode, which determines the demand of renewable and nonrenewab...
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ISBN:
(纸本)9783642166921
The multi-mode resource-constrained project scheduling problem with minimum and maximum time lags is considered in the paper. An activity is performed in a mode, which determines the demand of renewable and nonrenewable resources required for its processing and minimum and maximum time lags between adjacent activities. The goal is to find a mode assignment to the activities and their start times such that all constraints are satisfied and the project duration is minimized. Because the problem is NP-hard a population-learning algorithm (PLA2) is proposed to tackle the problem. PLA2 is a population-based approach which takes advantage of the features common to the social education system rather than to the evolutionary processes. The proposed approach perfectly suits for multi-agent systems because it is based on the idea of constructing a hybrid algorithm integrating different optimization techniques complementing each other and producing a synergetic effect. Results of the experiment were compared to the results published in projectscheduling Problem Library.
Purpose - The purpose of this paper is to develop a framework to optimize time, cost and quality in a multi-mode resource-constrained project scheduling environment. Design/methodology/approach - A case study approach...
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Purpose - The purpose of this paper is to develop a framework to optimize time, cost and quality in a multi-mode resource-constrained project scheduling environment. Design/methodology/approach - A case study approach identified the activity execution modes in building construction projects in India to support multi-mode resource-constrained project scheduling. The data required to compute time, cost and quality of each activity are compiled from real construction projects. A binary integer-programming model has been developed to perform multi-objective optimization and identify Pareto optimal solutions. The RR-PARETO3 algorithm was used to identify the best compromise trade-off solutions. The effectiveness of the proposed framework is demonstrated through sample case study projects. Findings - Results show that good compromise solutions are obtained through multi-objective optimization of time, cost and quality. Research limitations/implications - Case study data sets were collected only from eight building construction projects in India. Practical implications - It is feasible to adopt multi-objective optimization in practical construction projects using time, cost and quality as the objectives;Pareto surfaces help to quantify relationships among time, cost and quality. It is shown that cost can be reduced by increasing the duration, and quality can be improved only by increasing the cost. Originality/value - The use of different activity execution modes compiled from multiple projects in optimization is illustrated, and good compromise solutions for the multi-mode resource-constrained project scheduling problems using multi-objective optimization are identified.
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