An efficient solution approach for real-world driver scheduling problems in urban bus transportation

Most of the algorithmic engineering design optimisation approaches reported in the literature aims to find the best set of solutions within a quantitative (QT) search space of the given problem while ignoring related qualitative (QL) issues. These QL issues can be very important and by ignoring them in the optimisation search, can have expensive consequences especially for real world problems. This paper presents a new integrated design optimisation approach for QT and QL search space. The proposed solution approach is based on design of experiment methods and fuzzy logic principles for building the required QL models, and evolutionary multi-objective optimisation technique for solving the design problem. The proposed technique was applied to a two objectives rod rolling problem. The results obtained demonstrate that the proposed solution approach can be used to solve real world problems taking into account the related QL evaluation of the design problem.

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Mathematical models for a batch scheduling problem to minimize earliness and tardiness

Journal of Industrial Engineering and Management ◽

10.3926/jiem.2541 ◽

2018 ◽

Vol 11 (3) ◽

pp. 390 ◽

Cited By ~ 3

Author(s):

Basar Ogun ◽

Çigdem Alabas-Uslu

Keyword(s):

Mathematical Models ◽

Real World ◽

Lean Manufacturing ◽

Programming Model ◽

Computational Study ◽

Batch Scheduling ◽

Scheduling Problem ◽

Scheduling Problems ◽

Earliness And Tardiness ◽

Customer Orders

Purpose: Today’s manufacturing facilities are challenged by highly customized products and just in time manufacturing and delivery of these products. In this study, a batch scheduling problem is addressed to provide on-time completion of customer orders in the environment of lean manufacturing. The problem is to optimize partitioning of product components into batches and scheduling of the resulting batches where each customer order is received as a set of products made of various components.Design/methodology/approach: Three different mathematical models for minimization of total earliness and tardiness of customer orders are developed to provide on-time completion of customer orders and also, to avoid from inventory of final products. The first model is a non-linear integer programming model while the second is a linearized version of the first. Finally, to solve larger sized instances of the problem, an alternative linear integer model is presented.Findings: Computational study using a suit set of test instances showed that the alternative linear integer model is able to solve all test instances in varying sizes within quite shorter computer times comparing to the other two models. It was also showed that the alternative model can solve moderate sized real-world problems.Originality/value: The problem under study differentiates from existing batch scheduling problems in the literature since it includes new circumstances which may arise in real-world applications. This research, also, contributes the literature of batch scheduling problem by presenting new optimization models.

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A dynamic neighborhood based tabu search algorithm for real-world flight instructor scheduling problems

European Journal of Operational Research ◽

10.1016/j.ejor.2004.08.023 ◽

2006 ◽

Vol 169 (3) ◽

pp. 978-993 ◽

Cited By ~ 11

Author(s):

Jiefeng Xu ◽

Milind Sohoni ◽

Mike McCleery ◽

T. Glenn Bailey

Keyword(s):

Tabu Search ◽

Real World ◽

Search Algorithm ◽

Tabu Search Algorithm ◽

Scheduling Problems

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A Nature-Inspired Metaheuristic Approach for Generating Alternatives

Advanced Methodologies and Technologies in Business Operations and Management - Advances in Logistics, Operations, and Management Science ◽

10.4018/978-1-5225-7362-3.ch054 ◽

2019 ◽

pp. 722-733

Author(s):

Julian Scott Yeomans

Keyword(s):

Decision Making ◽

Mathematical Programming ◽

Real World ◽

System Performance ◽

Firefly Algorithm ◽

Multiple Solution ◽

Performance Criteria ◽

Design Issues ◽

Solution Approach ◽

Design Requirements

“Real-world” decision making often involves complex problems that are riddled with incompatible and inconsistent performance objectives. These problems typically possess competing design requirements which are very difficult—if not impossible—to quantify and capture at the time that any supporting decision models are constructed. There are invariably unmodeled design issues, not apparent during the time of model construction, which can greatly impact the acceptability of the model's solutions. Consequently, when solving many practical mathematical programming applications, it is generally preferable to formulate numerous quantifiably good alternatives that provide very different perspectives to the problem. This solution approach is referred to as modelling to generate alternatives (MGA). This study demonstrates how the nature-inspired firefly algorithm can be used to efficiently create multiple solution alternatives that both satisfy required system performance criteria and yet are maximally different in their decision spaces.

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A New Decision Support System for Optimal Integrated Project Scheduling and Resource Planning

Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering ◽

10.4018/978-1-7998-9023-2.ch065 ◽

2021 ◽

pp. 1367-1383

Author(s):

Amir Ahrari ◽

Ali Haghani

Keyword(s):

Resource Allocation ◽

Project Scheduling ◽

Efficient Solution ◽

Practical Problem ◽

Mathematical Formulation ◽

Optimal Solution ◽

Resource Planning ◽

Scheduling Problems ◽

Activity Scheduling ◽

Integrated Project

Two scheduling practices are commonly used depending on the availability of resources. When resources are not expensive, activities are scheduled and then resources are allocated until the available resources are exhausted. Then, iterative adjustments are applied to the resource allocation plan and the activities sequence to reach a feasible solution. Conversely, when expensive resources are involved, a resource allocation plan based on the economics of the resource is established and then activities are scheduled accordingly. However, Resource Constrained Scheduling Problems (RCSP) are not solved efficiently with either of these approaches. To find the optimal solution, activity scheduling and resource allocation should be formulated as an integrated optimization problem. Such models become numerically cumbersome for practical size problems and difficult to solve. In this article, a novel mathematical formulation and an efficient solution algorithm are proposed for solving RCSPs. Then, this framework is used for solving a practical problem in the context of the construction industry.

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Efficient Solution Approach to Maximum Flow Evacuation Planning Problem without Flow Conservation Aspect

Journal of the Institute of Engineering ◽

10.3126/jie.v13i1.20355 ◽

2018 ◽

Vol 13 (1) ◽

pp. 108-116

Author(s):

Phanindra Prasad Bhandari ◽

Shree Ram Khadka

Keyword(s):

Network Flow ◽

Efficient Solution ◽

Maximum Flow ◽

Evacuation Planning ◽

Planning Problem ◽

Intermediate Node ◽

Solution Approach ◽

Solution Strategies ◽

Source Sink ◽

Flow Conservation

An attempt of shifting as more people as possible and/or their logistics from a dangerous place to a safer place is an evacuation planning problem. Such problems modeled on network have been extensively studied and the various efficient solution procedures have been established. The solution strategies for these problems are based on source-sink path augmentation and the flow function satisfies the flow conservation at each intermediate node. Besides this, the network flow problem in which flow may not be conserved at node necessarily could also be used to model the evacuation planning problem. This paper proposes a model for maximum flow evacuation planning problem on a single-source-single-sink static network with integral arc capacities with holding capability of evacuees in the temporary shelter at intermediate nodes and extends the model into the dynamic case. Journal of the Institute of Engineering, 2017, 13(1): 108-116

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