A bid generation problem for combinatorial transportation auctions considering in-vehicle consolidations

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fang Yan ◽  
Kai Chen ◽  
Manjing Xu
Keyword(s):  
Computation Time ◽  
Mixed Integer ◽  
Small Scale ◽  
Second Phase ◽  
Two Phase ◽  
Content Type ◽  
Numerical Examples ◽  
Proposed Model ◽  
Vehicle Capacity ◽  
Generation Problem

PurposeThis paper studied a bid generation problem in combinatorial transportation auctions that considered in-vehicle consolidations. The purpose of this paper seeks to establish mixed integer programming to the most profitable transportation task packages.Design/methodology/approachThe authors proposes a mathematical model to identify the most profitable transportation task packages under vehicle capacity, flow balance and in-vehicle consolidation operational constraints, after which a two-phase heuristic algorithm was designed to solve the proposed model. In the first phase, a method was defined to compute bundle synergy, which was then combined with particle swarm optimization (PSO) to determine a satisfactory task package, and in the second phase, the PSO was adopted to program vehicle routings that considered in-vehicle consolidation.FindingsThree numerical examples were given to analyze the effects of the proposed model and method, with the first two small-scale examples coming from the same data base and the third being a larger scale example. The results showed that: (1) the proposed model was able to find a satisfactory solution for the three numerical examples; (2) the computation time was significantly shorter than the accurate algorithm and (3) considering in-vehicle consolidations operations could increase the carrier profits.Originality/valueThe highlights of this paper are summarized as following: (1) it considers in-vehicle consolidation when generating bids to maximize profits; (2) it simultaneously identifies the most valuable lane packages and reconstructs vehicle routes and (3) proposes a simple but effective synergy-based method to solve the model.

How can mixed integer linear programming assist dairy manufacturers by integrating supply decisions and production planning?

2021 ◽  
Vol 11 (2) ◽  
pp. 178-193
Author(s):  
Juliana Emidio ◽  
Rafael Lima ◽  
Camila Leal ◽  
Grasiele Madrona
Keyword(s):  
Linear Programming ◽  
Supply Chain ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Dairy Products ◽  
Raw Milk ◽  
Mixed Integer ◽  
Content Type ◽  
Proposed Model ◽  
By Products

PurposeThe dairy industry needs to make important decisions regarding its supply chain. In a context with many available suppliers, deciding which of them will be part of the supply chain and deciding when to buy raw milk is key to the supply chain performance. This study aims to propose a mathematical model to support milk supply decisions. In addition to determining which producers should be chosen as suppliers, the model decides on a milk pickup schedule over a planning horizon. The model addresses production decisions, inventory, setup and the use of by-products generated in the raw milk processing.Design/methodology/approachThe model was formulated using mixed integer linear programming, tested with randomly generated instances of various sizes and solved using the Gurobi Solver. Instances were generated using parameters obtained from a company that manufactures dairy products to test the model in a more realistic scenario.FindingsThe results show that the proposed model can be solved with real-world sized instances in short computational times and yielding high quality results. Hence, companies can adopt this model to reduce transportation, production and inventory costs by supporting decision making throughout their supply chains.Originality/valueThe novelty of the proposed model stems from the ability to integrate milk pickup and production planning of dairy products, thus being more comprehensive than the models currently available in the literature. Additionally, the model also considers by-products, which can be used as inputs for other products.

Evaluation of ecotourism sites: a GIS-based multi-criteria decision analysis

Kybernetes ◽  
2018 ◽  
Vol 47 (8) ◽  
pp. 1664-1686 ◽  
Author(s):  
Cihan Çetinkaya ◽  
Mehmet Kabak ◽  
Mehmet Erbaş ◽  
Eren Özceylan
Keyword(s):  
Black Sea ◽  
Real Data ◽  
The Black Sea ◽  
Second Phase ◽  
Content Type ◽  
Black Sea Region ◽  
Evaluation Approach ◽  
Third Phase ◽  
Proposed Model ◽  
Promethee Method

Purpose The aim of this study is to evaluate the potential geographic locations for ecotourism activities and to select the best one among alternatives. Design/methodology/approach The proposed model consists of four sequential phases. In the first phase, different geographic criteria are determined based on existing literature, and data are gathered using GIS. On equal criteria weighing, alternative locations are determined using GIS in the second phase. In the third phase, the identified criteria are weighted using analytical hierarchy process (AHP) by various stakeholders of potential ecotourism sites. In the fourth phase, the PROMETHEE method is applied to determine the best alternative based on the weighted criteria. Findings A framework including four sequential steps is proposed. Using real data from the Black Sea region in Turkey, the authors test the applicability of the evaluation approach and compare the best alternative obtained by the proposed method for nine cities in the region. Consequently, west of Sinop, east of Artvin and south of the Black Sea region are determined as very suitable locations for ecotourism. Research limitations/implications The first limitation of the study is considered the number of included criteria. Another limitation is the use of deterministic parameters that do not cope with uncertainty. Further research can be conducted for determining the optimum locations for different types of tourism, e.g. religion tourism, hunting tourism and golf tourism, for effective tourism planning. Practical implications The proposed approach can be applied to all area that cover the considered criteria. The approach has been tested in the Black Sea region (nine cities) in Turkey. Social implications Using the proposed approach, decision-makers can determine locations where environmentally responsible travel to natural areas to enjoy and appreciate nature that promotes conservation have a low visitor impact and provide for beneficially active socioeconomic involvement of local individuals. Originality/value To the best knowledge of the authors, this is the first study which applies a GIS-based multi-criteria decision-making approach for ecotourism site selection.

A fuzzy goal programming approach for selecting sustainable suppliers

2017 ◽  
Vol 24 (5) ◽  
pp. 1138-1165 ◽  
Author(s):  
Peeyush Pandey ◽  
Bhavin J. Shah ◽  
Hasmukh Gajjar
Keyword(s):  
Goal Programming ◽  
Supplier Selection ◽  
Qualitative Data ◽  
Fuzzy Goal Programming ◽  
Programming Approach ◽  
Two Phase ◽  
Content Type ◽  
Lean Practices ◽  
Proposed Model ◽  
Fuzzy Goal

Purpose Due to the ever increasing concern toward sustainability, suppliers nowadays are evaluated on the basis of environmental performances. The data on supplier’s performance are not always available in quantitative form and evaluating supplier on the basis of qualitative data is a challenging task. The purpose of this paper is to develop a framework for the selection of suppliers by evaluating them on the basis of both quantitative and qualitative data. Design/methodology/approach Literature on sustainability, green supply chain and lean practices related to supplier selection is critically reviewed. Based on this, a two phase fuzzy goal programming approach integrating hyperbolic membership function is proposed to solve the complex supplier selection problem. Findings Results obtained through the proposed approach are compared to the traditional models (Jadidi et al., 2014; Ozkok and Tiryaki, 2011; Zimmermann, 1978) of supplier selection and were found to be optimal as it achieves higher aspiration level. Practical implications The proposed model is adaptive to solve real world problems of supplier selection as all criteria do not possess the same weights, so the managers can change the criteria and their weights according to their requirement. Originality/value This paper provides the decision makers a robust framework to evaluate and select sustainable supplier based on both quantitative and qualitative data. The results obtained through the proposed model achieve greater satisfaction level as compared to those achieved by traditional methods.

A game theoretic approach to optimal pricing of flights and passengers at congested airports

2018 ◽  
Vol 13 (2) ◽  
pp. 434-454 ◽  
Author(s):  
Ata Allah Taleizadeh ◽  
Moeen Sammak Jalali ◽  
Shib Sankar Sana
Keyword(s):  
Large Scale ◽  
Congestion Pricing ◽  
Influential Factors ◽  
Future Research ◽  
Theoretic Approach ◽  
Content Type ◽  
Numerical Examples ◽  
Proposed Model ◽  
Managerial Implications ◽  
Game Theoretic

Purpose This paper aims to embark a mathematical model based on investigation and comparison of airport pricing policies under various types of competition, considering both per-passenger and per-flight charges at congested airports. Design/methodology/approach In this model, four-game theoretic strategies are assessed and closed-form formulas have been proved for each of the mentioned strategies. Numerical examples and graphical representations of the optimal solutions are provided to illustrate the models. Findings The rectitude of the presented formulas is evaluated with sensitivity analysis and numerical examples have been put forward. Finally, managerial implications are suggested by means of the proposed analysis. Research limitations/implications The represented model is inherently limited to investigate all the available and influential factors in the field of congestion pricing. With this regard, several studies can be implemented as the future research of this study. The applications of other game theoretic approaches such as Cartel games and its combination with the four mentioned games seem to be worthwhile. Moreover, it is recommended to investigate the effectiveness of the proposed model and formulations with a large-scale database. Originality/value The authors formulate a novel strategy that put forwards a four-game theoretic strategy, which helps managers to select the best suitable ones for their specific airline and/or air traveling companies. The authors find that by means of the proposed model, the application of Stackelberg–Bertrand behavior in the field of airport congestion pricing will rebound to a more profitable strategy in contrast with the other three represented methods.

Operations strategy of cloud-based firms: achieving firm growth in the Big Data era

2019 ◽  
Vol 40 (6) ◽  
pp. 873-896 ◽  
Author(s):  
Yongyi Shou ◽  
Xinyu Zhao ◽  
Lujie Chen
Keyword(s):  
Big Data ◽  
Content Analysis ◽  
Operations Management ◽  
Firm Growth ◽  
Seemingly Unrelated Regression ◽  
Second Phase ◽  
Operations Strategy ◽  
Two Phase ◽  
Content Type ◽  
Operations Capabilities

Purpose Cloud computing is a major enabling technology for Industry 4.0 and the Big Data era. However, cloud-based firms, who establish their businesses on cloud platforms, have received scant attention in the extant operations management (OM) literature. To narrow this gap, the purpose of this paper is to investigate cloud-based firms from an operations strategy perspective. Design/methodology/approach A two-phase multi-method approach was adopted. In the first phase, content analysis of 27 reports from cloud-based firms was conducted, aided by text mining keyword extraction. Two data-related operations capabilities were identified and hypotheses were posited regarding the relationships between data resources (DR), operations capabilities and firm growth (FG). In the second phase, a sample of 190 cloud-based firms was collected. Seemingly unrelated regression and bootstrapping method were employed to test the proposed hypotheses using the survey data. Findings The content analysis indicates data as a key resource and both data processing capability and data transformational capability as critical operations capabilities of cloud-based firms. FG is regarded as a top priority in the cloud context. The regression results indicate that DR and the two capabilities contribute to the growth of cloud-based firms. Moreover, a follow-up bootstrapping analysis reveals that the mediating effects of the two capabilities vary between different types of FG. Originality/value To the authors’ best knowledge, this is one of the first OM studies on cloud-based firms. This study extends the operations strategy literature by identifying and testing the key operations capabilities and priorities of cloud-based firms. It also provides insightful implications for industrial practitioners.

scholarly journals Drone-Based Parcel Delivery Using the Rooftops of City Buildings: Model and Solution

2020 ◽  
Vol 10 (12) ◽  
pp. 4362 ◽  
Author(s):  
Junsu Kim ◽  
Hongbin Moon ◽  
Hosang Jung
Keyword(s):  
Urban Areas ◽  
Programming Model ◽  
Computation Time ◽  
Intelligent Transportation ◽  
Mixed Integer ◽  
Operation Planning ◽  
Logistics System ◽  
Proposed Model ◽  
Optimality Gap ◽  
Good Operation

In general, the demand for delivery cannot be fulfilled efficiently due to the excessive traffic in dense urban areas. Therefore, many innovative concepts for intelligent transportation of freight have recently been developed. One of these concepts relies on drone-based parcel delivery using rooftops of city buildings. To apply drone logistics system in cities, the operation design should be adequately prepared. In this regard, a mixed integer programming model for drone operation planning and a heuristic based on block stacking are newly proposed to provide solutions. Additionally, numerical experiments with three different problem sizes are conducted to check the feasibility of the proposed model and to assess the performance of the proposed heuristic. The experimental results show that the proposed model seems to be viable and that the developed heuristic provides very good operation plans in terms of the optimality gap and the computation time.

A novel discontinuous Galerkin model for two-phase flow in porous media using an improved IMPES method

2016 ◽  
Vol 26 (1) ◽  
pp. 284-306 ◽  
Author(s):  
Mehdi Jamei ◽  
H Ghafouri
Keyword(s):  
Porous Media ◽  
Discontinuous Galerkin ◽  
Numerical Scheme ◽  
Two Phase Flow ◽  
Weighted Average ◽  
Computation Time ◽  
Flow In Porous Media ◽  
Phase Flow ◽  
Two Phase ◽  
Content Type

Purpose – The purpose of this paper is to present an efficient improved version of Implicit Pressure-Explicit Saturation (IMPES) method for the solution of incompressible two-phase flow model based on the discontinuous Galerkin (DG) numerical scheme. Design/methodology/approach – The governing equations, based on the wetting-phase pressure-saturation formulation, are discretized using various primal DG schemes. The authors use H(div) velocity reconstruction in Raviart-Thomas space (RT_0 and RT_1), the weighted average formulation, and the scaled penalties to improve the spatial discretization. It uses a new improved IMPES approach, by using the second-order explicit Total Variation Diminishing Runge-Kutta (TVD-RK) as temporal discretization of the saturation equation. The main purpose of this time stepping technique is to speed up computation without losing accuracy, thus to increase the efficiency of the method. Findings – Utilizing pressure internal interpolation technique in the improved IMPES scheme can reduce CPU time. Combining the TVD property with a strong multi-dimensional slope limiter namely, modified Chavent-Jaffre leads to a non-oscillatory scheme even in coarse grids and highly heterogeneous porous media. Research limitations/implications – The presented locally conservative scheme can be applied only in 2D incompressible two-phase flow modeling in non-deformable porous media. In addition, the capillary pressure discontinuity between two adjacent rock types assumed to be negligible. Practical implications – The proposed numerical scheme can be efficiently used to model the incompressible two-phase flow in secondary recovery of petroleum reservoirs and tracing immiscible contamination in aquifers. Originality/value – The paper describes a novel version of the DG two-phase flow which illustrates the effects of improvements in special discretization. Also the new improved IMPES approach used reduces the computation time. The non-oscillatory scheme is an efficient algorithm as it maintains accuracy and saves computation time.

Structure and mechanical behavior of Big Area Additive Manufacturing (BAAM) materials

2017 ◽  
Vol 23 (1) ◽  
pp. 181-189 ◽  
Author(s):  
Chad E. Duty ◽  
Vlastimil Kunc ◽  
Brett Compton ◽  
Brian Post ◽  
Donald Erdman ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Mechanical Performance ◽  
Research Effort ◽  
Small Scale ◽  
Second Phase ◽  
Initial Development ◽  
Imperfect Contact ◽  
Content Type ◽  
Oak Ridge ◽  
Printed Materials

Purpose This paper aims to investigate the deposited structure and mechanical performance of printed materials obtained during initial development of the Big Area Additive Manufacturing (BAAM) system at Oak Ridge National Laboratory. Issues unique to large-scale polymer deposition are identified and presented to reduce the learning curve for the development of similar systems. Design/methodology/approach Although the BAAM’s individual extruded bead is 10-20× larger (∼9 mm) than the typical small-scale systems, the overall characteristics of the deposited material are very similar. This study relates the structure of BAAM materials to the material composition, deposition parameters and resulting mechanical performance. Findings Materials investigated during initial trials are suitable for stiffness-limited applications. The strength of printed materials can be significantly reduced by voids and imperfect fusion between layers. Deposited material was found to have voids between adjacent beads and micro-porosity within a given bead. Failure generally occurs at interfaces between adjacent beads and successive layers, indicating imperfect contact area and polymer fusion. Practical implications The incorporation of second-phase reinforcement in printed materials can significantly improve stiffness but can result in notable anisotropy that needs to be accounted for in the design of BAAM-printed structures. Originality/value This initial evaluation of BAAM-deposited structures and mechanical performance will guide the current research effort for improving interlaminar strength and process control.

Green supplier selection using an AHP-Entropy-TOPSIS framework

2015 ◽  
Vol 20 (3) ◽  
pp. 327-340 ◽  
Author(s):  
James Freeman ◽  
Tao Chen
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Selection Criteria ◽  
Second Phase ◽  
Structured Interviews ◽  
Entropy Weight ◽  
Two Phase ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Green Supplier Selection

Purpose – This paper aims to focus on development of a green supplier selection model using an index system based on a combination of traditional supplier and environmental supplier selection criteria. Strategies that balance economic and environmental performance are increasingly sought after as enterprises that increasingly focus on the sustainability of their operations. Green supply chain management (GSCM) in particular, enables the integration of environmentally friendly suppliers into the supply chain to be systematised to fit with specific environmental regulations and policies. More persuasively, GSCM allows enterprises to improve profits whilst lowering impacts on the global environment. Design/methodology/approach – A two-phase survey approach was adopted for the research. For the first phase, semi-structured interviews with senior management representatives of the case company – a Chinese-based electronic machinery manufacturer – were used to determine green supplier selection criteria. For the second phase, a two-part questionnaire survey was undertaken, the first part providing the data for an analytic hierarchy process (AHP) analysis of the first-phase criteria and the second with collecting data for an Entropy weight analysis. The resultant AHP and Entropy weights were then combined to form compromised weights – which, using technique for order preference by similarity to the ideal solution (TOPSIS) methodology, were translated into preferential rankings of suppliers. Findings – Senior managers were found to rank traditional criteria more highly than environmental alternatives – the implication being that for the company, concerned, it may take some time before environmental awareness is fully assimilated into GSCM practice. Originality/value – The paper moves us a significant step closer to the application more widely, of innovative AHP-Entropy/TOPSIS methodology to real-world SCM problems.

Work continuity constraints in repetitive project scheduling considering soft logic

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xin Zou ◽  
Guangchuan Wu ◽  
Qian Zhang
Keyword(s):  
Programming Model ◽  
Mixed Integer ◽  
Future Research ◽  
Small Scale ◽  
Content Type ◽  
Project Duration ◽  
Additional Information ◽  
Work Interruptions ◽  
Conflicting Objectives ◽  
Soft Logic

PurposeRepetitive projects play an important role in the construction industry. A crucial point in scheduling this type of project lies in enabling timely movement of crews from unit to unit so as to minimize the adverse effect of work interruptions on both time and cost. This paper aims to examine a repetitive scheduling problem with work continuity constraints, involving a tradeoff among project duration, work interruptions and total project cost (TPC). To enhance flexibility and practicability, multi-crew execution is considered and the logic relation between units is allowed to be changed arbitrarily. That is, soft logic is considered.Design/methodology/approachThis paper proposes a multi-objective mixed-integer linear programming model with the capability of yielding the optimal tradeoff among three conflicting objectives. An efficient version of the e-constraint algorithm is customized to solve the model. This model is validated based on two case studies involving a small-scale and a practical-scale project, and the influence of using soft logic on project duration and total cost is analyzed via computational experiments.FindingsUsing soft logic provides more flexibility in minimizing project duration, work interruptions and TPC, especial for non-typical projects with a high percentage of non-typical activities.Research limitations/implicationsThe main limitation of the proposed model fails to consider the learning-forgetting phenomenon, which provides space for future research.Practical implicationsThis study assists practitioners in determining the “most preferred” schedule once additional information is provided.Originality/valueThis paper presents a new soft logic-based mathematical programming model to schedule repetitive projects with the goal of optimizing three conflicting objectives simultaneously.

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