Purpose - The purpose of this paper is to develop new model formulation for reducing the workload in pre-batching at a manufacturer of flavors and fragrances, by optimally assigning ingredients to different storage ty...
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Purpose - The purpose of this paper is to develop new model formulation for reducing the workload in pre-batching at a manufacturer of flavors and fragrances, by optimally assigning ingredients to different storage types, taking into account past usage of ingredients and several restrictions about volumes and number of storage units. Design/methodology/approach - Two models were developed, using mathematical programming, accommodating either fixed or variable shelf settings in vertical carousel storage, along with other varying storage types. The models were validated, yielding a sizeable reduction in workload, and run under varying scenarios of storage additions to reduce workload even further. Findings - For different storage addition scenarios, application of the new model formulation yielded a reduction of 22 percent in workload. In addition, aside from space savings, approximately 40 percent of refill order total waiting time was reduced due to improved allocation. Research limitations/implications - The authors' analysis was limited by considering direct cost savings only. Yet, reduced workloads in pre-batching may also yield indirect cost savings, such as reduced quality costs, inventory costs, and investment savings by not having to extend the pre-batching area. Such considerations may be addressed in future research, provided data on indirect savings are available. Practical implications - While intuitive storage allocation overloads the pre-batching department and increases space utilization, suggesting an incorrect perception that more personnel and space are needed, the proposed approach provides a better alternative through optimized allocations. Originality/value - The present paper adds to the literature on carousel storage location by explicitly addressing the storage sizing issue, as well as workload balancing.
This paper deals with preemptive priority based multi-objective network design problems in which construction times together with travel costs are taken into account. These cost and time objective functions are ordere...
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This paper deals with preemptive priority based multi-objective network design problems in which construction times together with travel costs are taken into account. These cost and time objective functions are ordered lexicographically with respect to manager's strategies in order to decrease total cost and total construction time of the network. To solve this preemptive problem, instead of the standard sequential approach, a modified Benders decomposition algorithm is developed. It is proved that this algorithm decreases the (expected) number of computations and so this algorithm is efficient for large-scale network design problems.
We report and analyze the results of our computational testing of branch-and-cut for piecewise linear optimization using the cutting planes given recently by Zhao and de Farias. Besides evaluating the performance of t...
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We report and analyze the results of our computational testing of branch-and-cut for piecewise linear optimization using the cutting planes given recently by Zhao and de Farias. Besides evaluating the performance of the cuts, we evaluate the effect of formulation on the performance of branch-and-cut. Finally, we report and analyze results on piecewise linear optimization problems with semi-continuous constraints.
Researchers in the life sciences (i.e., healthcare and agriculture) commonly use heuristics to process and interpret the vast amount of available DNA sequence data. The application of discrete optimization techniques,...
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Researchers in the life sciences (i.e., healthcare and agriculture) commonly use heuristics to process and interpret the vast amount of available DNA sequence data. The application of discrete optimization techniques, such as mixed-integer programming (MIP), remains largely unexplored and has the potential to transform the field. This paper reports on the successful use of MIP to optimize experimental design in a practical genetics application. More generally, our results illustrate the potential benefits of using MIP for subset selection problems in genetics.
We investigate a generalized version of the prize collecting Steiner tree problem (PCSTP), where each node of a given weighted graph is associated with a prize as well as a penalty cost. The problem is to find a tree ...
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We investigate a generalized version of the prize collecting Steiner tree problem (PCSTP), where each node of a given weighted graph is associated with a prize as well as a penalty cost. The problem is to find a tree spanning a subset of nodes that collects a total prize not less than a given quota Q, such that the sum of the weights of the edges in the tree plus the sum of the penalties of those nodes that are not covered by the tree is minimized. We formulate several compact mixed-integer programming models for the PCSTP and enhance them by appending valid inequalities, lifting constraints, or reformulating the model using the Reformulation-Linearization Technique (RLT). We also conduct a theoretical comparison of the relative strengths of the associated LP relaxations. Extensive results are presented using a large set of benchmark instances to compare the different formulations. In particular, a proposed hybrid compact formulation approach is shown to provide optimal or very near-optimal solutions for instances having up to 2500 nodes and 3125 edges. (C) 2011 Elsevier B.V. All rights reserved.
作者：
Drachev, PavelRAS
SB Energy Syst Inst Lab Dev Elect Power Syst Irkutsk Russia
The unbundling of the electricity business has raised new challenges that the restructured industry faces. Transmission system provides nondiscriminatory, effective and competitive environment for participants. Hence,...
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ISBN:
(纸本)9781467356688
The unbundling of the electricity business has raised new challenges that the restructured industry faces. Transmission system provides nondiscriminatory, effective and competitive environment for participants. Hence, the traditional cost-minimization formulation is no longer suitable to solve transmission expansion problem in market conditions. To evaluate efficiency of network expansion the comparison of investment and social welfare is needed. This requires a coordinated approach to the optimization of the generation and transmission operation and development. The model considered in the paper allows taking into account discrete nature of investment, different operating conditions while modeling market with perfect competition. The proposed methodology is applied to the network of Unified energy systems of Russia based on the real data.
This paper aims to investigate the benefit of deploying battery energy storage system (BESS) in a power system for reducing production cost, shaving peak-load and providing reserve support. A BESS model is built which...
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ISBN:
(纸本)9781479913039
This paper aims to investigate the benefit of deploying battery energy storage system (BESS) in a power system for reducing production cost, shaving peak-load and providing reserve support. A BESS model is built which takes into account the charging and discharging efficiencies, charging/discharging power limits, and reserve capacity limits. This model is incorporated into the security-constrained unit commitment (SCUC) problem. The new SCUC problem is solved to optimally allocate the charging and discharging power and reserve capacity of each BESS. Tests are carried out on the IEEE 24-bus system and simulation results show that lower operational cost can be achieved by using BESS for both peak-load shaving/shifting and reserve support.
This paper analyzes the impact of natural gas supply, increased penetration of renewable energy sources and shifting demand trends due to tight financial conditions on generating unit maintenance scheduling. The main ...
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ISBN:
(纸本)9781467356688
This paper analyzes the impact of natural gas supply, increased penetration of renewable energy sources and shifting demand trends due to tight financial conditions on generating unit maintenance scheduling. The main focus is on the increased importance of enhancing unit availability in periods of concurrent peak electricity and natural gas demand and limited RES contribution, through proper adjustment of power system maintenance rules. In power systems with peak demand in summer and high photovoltaic penetration, this translates into enforcing unit availability during winter. A detailed mixed-integer linear programming model for the yearly maintenance scheduling of a System Operator is developed with GAMS/CPLEX in order to evaluate modifications in maintenance rules. The same model is used to assess the consequences of a short-term natural gas shortage contingency scenario, given the maintenance decisions of the yearly scheduling process. The method is applied to the Greek power system.
This article presents a new model for constructing monthly clinic schedules for interns and residents (i.e., housestaff) training in Internal Medicine. Clinical experiences during the three years of residency occur in...
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This article presents a new model for constructing monthly clinic schedules for interns and residents (i.e., housestaff) training in Internal Medicine. Clinical experiences during the three years of residency occur in inpatient and outpatient settings, and on generalist and specialist clinical services. These experiences include spending time in a primary care setting caring for an assigned group of patients over time. Housestaff rotate through different clinical experiences monthly, with their primary care clinic time overlaid longitudinally on these other clinical services. The exact amount of primary care time spent varies between clinical rotations. In fact, it is the variable clinic hour requirements that drive the scheduling process, and is what distinguishes our problem from most personnel scheduling problems. Typically, staff schedules are driven by shift or hourly demand and are designed to minimize some measure of cost. The objective in our work is to both maximize clinic utilization and minimize the number of violations of a prioritized set of goals while ensuring that certain clinic-level and individual constraints are satisfied. The corresponding problem is formulated as an integer goal program in which several of the hard constraints are temporarily allowed to be violated to avoid infeasibility. To find solutions, a three-phase methodology is proposed. In the first phase (pre-processing step), clinic assignments for a subset of the housestaff are either fixed or excluded each month in light of restrictions imposed by their current rotation. In the second phase, tentative solutions are obtained with a commercial solver. In the final phase (post-processing step), all violations of the relaxed hard constraints are removed and an attempt is made to lexicographically reduce violations of the major goals. The effectiveness of the methodology is demonstrated by analyzing eight monthly rosters provided by the Internal Medicine Residency Program at the Universi
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