Technical Sessions – Monday July 11
Technical Sessions – Monday July 11
Technical Sessions – Monday July 11
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MB-16 IFORS 20<strong>11</strong> - Melbourne<br />
Imagery satellites serve purposes from intelligence analysis to environmental<br />
analysis. Demand for imagery however far exceeds available satellites. The<br />
multi-satellite scheduling problem determines which targets should be imaged<br />
by which satellite and when. We propose a new cluster-route-schedule approach<br />
which first groups targets into smaller clusters, next uses column generation<br />
to determine which clusters each satellite should image and when, and<br />
then assigns individual targets within each cluster. The goal is to maximize the<br />
overall utility of the imagery subject to physical, orbit, and energy constraints.<br />
Computational results are presented and demonstrated on Google Earth.<br />
� MB-16<br />
<strong>Monday</strong>, 14:00-15:30<br />
Meeting Room 209<br />
Scheduling Service and Manufacturing<br />
Systems<br />
Stream: Scheduling<br />
Invited session<br />
Chair: Chelliah Sriskandarajah, School of Management, SM30,<br />
University of Texas at Dallas, 800 West Campbell Road, 75080,<br />
Richardson, Texas, United States, chelliah@utdallas.edu<br />
1 - Minimization of Earliness, Tardiness and Due Date<br />
Penalties on Uniform Parallel Machines with Identical<br />
Jobs<br />
Inna Drobouchevitch, Korea University Business School, Seoul,<br />
Korea, Republic Of, innadro@hotmail.com, Jeffrey B. Sidney<br />
We consider a problem of scheduling n identical nonpreemptive jobs with a<br />
common due date on m uniform parallel machines. The objective is to determine<br />
an optimal value of the due date and an optimal allocation of jobs onto<br />
machines so as to minimize a total cost function, which is the function of earliness,<br />
tardiness and due date values. For the problem under study, we establish<br />
a set of properties of an optimal solution and develop a polynomial-time algorithm<br />
to solve the problem.<br />
2 - Optimal Scheduling of Mobile Advertisements<br />
Subodha Kumar, Mays Business School, Texas A&M University,<br />
Wehner 301F - 4217 TAMU, 77843, College Station, TX, United<br />
States, subodha@tamu.edu, Bandyopadhyay Tridib, Milind<br />
Dawande, Vijay Mookerjee<br />
Mobile wireless devices are increasingly becoming powerful platform for advertising<br />
because they can be used to track physical location of its users. However,<br />
the ineffective advertisements not only increase the cost to the advertisers,<br />
but may also create a negative value for the item. Hence, the firms need to make<br />
the advertising decisions judiciously. We optimize the decisions for a large marketing<br />
firm which needs to maximize the effectiveness of advertisements in a<br />
given planning horizon.<br />
3 - Batch Scheduling to Minimize Inventory Holding and<br />
Delivery Costs with Release Time Constraints<br />
Esaignani Selvarajah, Odette School of Business, University of<br />
Windsor, 401 Sunset Avenue, N9B 3P4, Windsor, Ontario,<br />
Canada, selvare@uwindsor.ca, Rui Zhang<br />
A manufacturer receives jobs from suppliers, and produces and delivers final<br />
products to customers in batches. The manufacturer is modeled as a single machine<br />
in the supply chain and the problem is modelled as minimizing the sum of<br />
weighted flow time and the batch delivery costs. Since the problem is strongly<br />
NP-hard, we first analyze some polynomially solvable special problems. Then<br />
we develop a heuristic algorithm to solve the general problem. The computational<br />
experiments show that the solutions of the heuristic algorithm are close<br />
to optimal solution.<br />
4 - Fresh Product Sales Planning: As a Whole or As Parts?<br />
Xiaolin Xu, Business Administration, Nanjing University,<br />
Anzhong Building, School of Business, 210093, Nanjing,<br />
Jiangsu, China, xuxl@nju.edu.cn<br />
We consider a fresh produce supplier, who can sell his product either as a whole<br />
in the spot market or as two separate parts through a mixed channel. The two<br />
parts differs in demand, with one (say part 1) dominating the other (say part 2).<br />
If selling as parts, the supplier decides his wholesale price based on its effect on<br />
the procurement quantity to part 1 retailer, taking into account the spot demand<br />
uncertainty of part 2. We study under what situations which strategy should be<br />
adopted by the supplier.<br />
18<br />
� MB-17<br />
<strong>Monday</strong>, 14:00-15:30<br />
Meeting Room 214<br />
Artificial Intelligence for MCDA<br />
Stream: Multicriteria Decision Analysis and<br />
Multiobjective Optimisation<br />
Invited session<br />
Chair: Constantin Zopounidis, Dept. of Production Engineering and<br />
Management, <strong>Technical</strong> University of Crete, University Campus,<br />
73100, Chania, Greece, kostas@dpem.tuc.gr<br />
1 - Missing Item Scores Estimation in Incomplete Reciprocal<br />
Pairwise Comparison Matrix<br />
Yi Peng, School of Management and Economics, University of<br />
Electronic Science and Technology of China, 610054, Chengdu,<br />
China, pengyicd@gmail.com, Daji Ergu, Gang Kou, Yong Shi<br />
An intelligence processing technique is proposed to intelligently calculate and<br />
estimate the missing item scores of an incomplete reciprocal pairwise comparison<br />
matrix (IRPCM). A scale format is used to design the score items for<br />
a comparison matrix. Besides, an induced bias matrix model (IBMM) is proposed<br />
to estimate the missing item scores of the reciprocal pairwise comparison<br />
matrix. The theorems of the IBMM are developed, some different cases with<br />
different missing numbers in a general IRPCM of order four are analyzed, and<br />
some numerical examples are used to illustrate the proposed model.<br />
2 - Theoretical Analysis on Cut-off Policy in Credit Scoring<br />
- Linear Programming Models with Changeable Right<br />
Hand Parameters<br />
Jing He, School of Engineering and Science, Victoria University,<br />
PO Box 14428, Melbourne, VIC 8001, Australia,<br />
jing.he@vu.edu.au, Yanchun Zhang, Yong Shi, Guangyan Huang<br />
Linear discriminant models consider two objectives: firstly, the minimal distances<br />
of observations from the critical value are maximized (MMD); the second<br />
minimizes the sum of the deviations (MSD) of the observations. Given a<br />
threshold, the best data separation can be selected from results determined by<br />
different b (cutoff or right-hand parameter) values. We utilize multiple criteria<br />
and multiple constraint levels linear programming model to explore LP models<br />
with changeable right hand parameters (b). We will study how to find best<br />
solutions in general and specific linear discriminant cases.<br />
� MB-18<br />
<strong>Monday</strong>, 14:00-15:30<br />
Meeting Room 215<br />
DEA Theoretical Development - 1<br />
Stream: Data Envelopment Analysis<br />
Invited session<br />
Chair: Francisco Lopez, School of Business, Macon State College,<br />
100 College Station, 31206, Macon, GA, United States,<br />
francisco.lopez@maconstate.edu<br />
1 - Incorporate Dual-role Factors in DEA<br />
Wen-Chih Chen, Dept of Industrial Engineering and<br />
Management, National Chiao Tung University, 1001 Ta Hsueh<br />
Rd., 300, Hsinchu, Taiwan, wenchih@faculty.nctu.edu.tw<br />
Typical DEA studies consider production processes of transforming many inputs<br />
to various outputs. In some cases, however, some factors may be considered<br />
as both inputs and outputs; these factors are referred to as dual-role<br />
factors. For example, research funding is an important output criterion while<br />
it is a resource to strengthen academic performance of a university. This study<br />
investigates dual-role factors in DEA. Rather than proposing an ad hoc model<br />
directly, an axiomatic approach is used. Therefore, our model is theoretically<br />
well-defined and intuitively obvious.